System for Wireless, Motion and Position-Sensing, Integrating Radiation Sensor and Energy Harvester for Occupational and Environmental Dosimetry

ABSTRACT

Described are a method and apparatus for determining based on motion data when an individual wearing a dosimeter is active. Also described are a method and apparatus for determining based on motion data whether an individual was wearing a dosimeter when the dosimeter was exposed to radiation. Also described are a method and apparatus for determining based on motion data whether a dosimeter was in a particular location when the dosimeter was exposed to radiation. Also described are a method and apparatus for determining based on motion data where on the body of an individual the individual was wearing a dosimeter when the dosimeter was exposed to radiation. Also described are a method and apparatus for determining based on motion data the probability that an individual is wearing a dosimeter that is assigned to the individual.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims benefit of priority to and is acontinuation-in-part of U.S. patent application Ser. No. 14/274,082 toValentino et al., entitled, “ENERGY HARVESTER FOR WIRELESS, MOTION ANDPOSITION-SENSING, INTEGRATING RADIATION SENSOR FOR OCCUPATIONAL ANDENVIRONMENTAL DOSIMETRY,” filed May 9, 2014, now pending, which claimsbenefit of priority to U.S. Provisional Patent Application No.61/821,683 filed May 9, 2013 which is incorporated by reference in itsentirety. This application claims benefit of priority to and is acontinuation-in-part of U.S. patent application Ser. No. 13/906,553 toValentino et al., entitled, “WIRELESS, MOTION AND POSITION-SENSING,INTEGRATING RADIATION SENSOR FOR OCCUPATIONAL AND ENVIRONMENTALDOSIMETRY,” filed May 31, 2013, now pending, which claims benefit ofpriority to U.S. Provisional Patent Application No. 61/654,162 toValentino et al. entitled, “WIRELESS, MOTION AND POSITION-SENSING,INTEGRATING RADIATION SENSOR FOR OCCUPATIONAL AND ENVIRONMENTALDOSIMETRY,” filed Jun. 1, 2012 which is hereby incorporated by referencein its entirety.

BACKGROUND

1. Field of the Invention

The present invention relates to measuring the motion activity of aperson that is being monitored for exposure to a measurable quantity ofa potentially hazardous entity or material such as a radiation source, achemical substance, or a biological agent.

2. Background of the Invention

A problem with respect to radiation sensors that are worn by anindividual, such in the form of a personal dosimeter, is that it hasbeen difficult to determine if the individual has been wearing thedosimeter, or how long the individual has been wearing the dosimeter.The correlation of motion activity, time, spatial position, and ameasured quantity of hazardous material is critically important indetermining if the exposure occurred during the course of normalactivity, and if it occurred during working hours at the work location.This information can be used to verify and ensure compliance withoccupational monitoring and other regulatory requirements, and toenhance the effectiveness of occupational safety programs.

SUMMARY

According to a first broad aspect, the present invention provides amethod comprising the following steps: (a) determining a first period oftime that an individual has been active based on motion data for adosimeter worn by the individual and time data associated with themotion data, and (b) reporting the first period of time the individualhas been active via a visual display device and/or via saving the firstperiod of time the individual has been active to a storage medium,wherein the dosimeter comprises one or more motion sensors forgenerating the motion data.

According to a second broad aspect, the present invention provides amethod comprising the following steps: (a) determining whether anindividual was wearing a dosimeter during a monitored period based uponmotion and time data obtained from the dosimeter, and (b) determiningwhether an individual was wearing the dosimeter when the dosimeter wasexposed to one or more radiation sources based upon measured radiationdosage data for the dosimeter, motion data for the dosimeter, time dataassociated with the radiation dosage data, and time data associated withthe motion data, (c) reporting whether the dosimeter was worn during amonitored period via display on a visual display device and/or viasaving whether the individual was wearing a dosimeter when the dosimeterwas exposed to one or more radiation sources to a storage medium,wherein the dosimeter comprises one or more motion sensors forgenerating the motion data, and (d) reporting whether the individual waswearing a dosimeter when the dosimeter was exposed to one or moreradiation sources via display on a visual display device and/or viasaving whether the individual was wearing a dosimeter when the dosimeterwas exposed to one or more radiation doses to a storage medium, whereinthe dosimeter comprises one or more motion sensors for generating themotion data.

According to a third broad aspect, the present invention provides amethod comprising the following steps: (a) determining a dosimeter wasin a location when the dosimeter was exposed to one or more radiationdoses based on radiation dosage data for the dosimeter, motion data forthe dosimeter, time data associated with the radiation dosage data, timedata associated with the motion data, and location data and locationdata for the dosimeter, and (b) reporting whether the dosimeter was inthe location when the dosimeter was exposed to one or more radiationdoses via display on a visual display device and/or via saving whetherthe dosimeter was in the location when the dosimeter was exposed to oneor more radiation doses to a storage medium, wherein the dosimetercomprises one or more motion sensors for generating the motion data.

According to a fourth broad aspect, the present invention provides amethod comprising the following steps: (a) determining where on a bodyof an individual that the individual was wearing a dosimeter when thedosimeter was exposed to one or more radiation doses based motion datafor the dosimeter and time data associated with the motion data, and (b)reporting where on the body of the individual the individual was wearinga dosimeter when the dosimeter was exposed to one or more radiationdoses via display on a visual display device and/or via saving whetherthe individual was wearing a dosimeter when the dosimeter was exposed toone or more radiation doses to a storage medium, wherein the dosimetercomprises one or more motion sensors for generating the motion data.

According to a fifth broad aspect, the present invention provides amethod comprising the following steps: (a) determining a probabilitythat an individual wearing a dosimeter is the individual to whom thedosimeter is assigned based on motion data for the dosimeter, and (b)reporting the probability that the individual wearing the dosimeter isthe individual to whom the dosimeter is assigned via display on a visualdisplay device and/or via saving the probability that the individualwearing the dosimeter is the individual to whom the dosimeter isassigned to a storage medium, wherein the dosimeter comprises one ormore motion sensors for generating the motion data.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated herein and constitutepart of this specification, illustrate exemplary embodiments of theinvention, and, together with the general description given above andthe detailed description given below, serve to explain the features ofthe invention.

FIG. 1 illustrates a split sphere encapsulating “filtration bubble” fora plurality of ionizing radiation sensors according to an exemplaryembodiment of the present invention;

FIG. 2 illustrates an integrated sensor module according to an exemplaryembodiment of the present invention;

FIG. 3 illustrates a remote sensor network according to an exemplaryembodiment of the present invention;

FIG. 4 illustrates an autonomous mobile sensor (AMS) network accordingto an exemplary embodiment of the present invention;

FIG. 5 illustrates an integrated sensor module logic flow according toan exemplary embodiment of the present invention;

FIG. 6 illustrates a sensor readout logic flow according to an exemplaryembodiment of the present invention;

FIG. 7 illustrates a point of exposure readout logic flow according toan exemplary embodiment of the present invention;

FIG. 8 illustrates a wireless sensor base station configurationaccording to an exemplary embodiment of the present invention;

FIG. 9 illustrates a computational procedure according to an exemplaryembodiment of the present invention;

FIG. 10 illustrates a flowchart of the disclosed computational procedurefor employing an algorithm according to an exemplary embodiment of thepresent invention.

FIG. 11 illustrates an integrated sensor module according to anexemplary embodiment of the present invention.

FIG. 12 is an illustrative graph of motion data from an accelerometerfor a dosimeter worn by an individual.

FIG. 13 is an illustrative graph of motion data from an accelerometerfor a dosimeter worn by an individual while the individual is sittingwith minimal or no motion.

FIG. 14 is an illustrative graph of motion data from an accelerometerfor a dosimeter worn by an individual while the individual walking.

FIG. 15 is an illustrative graph of motion data from an accelerometerfor dosimeter worn by an individual who is standing still, then wavingthe individual's arms, then standing still.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Definitions

Where the definition of terms departs from the commonly used meaning ofthe term, applicant intends to utilize the definitions provided below,unless specifically indicated.

For the purposes of the present invention, directional terms such as“top”, “bottom”, “upper”, “lower”, “above”, “below”, “left”, “right”,“horizontal”, “vertical”, “upward”, “downward”, etc., are merely usedfor convenience in describing the various embodiments of the presentinvention.

For purposes of the present invention, a value or property is “based” ona particular value, property, the satisfaction of a condition or otherfactor if that value is derived by performing a mathematical calculationor logical decision using that value, property or other factor.

For the purposes of the present invention, the term “accelerometer”refers to an electromechanical device for measuring acceleration forcesincluding static or dynamic forces. An accelerometer measures properacceleration, which is the acceleration it experiences relative to freefall and is the acceleration felt by people and objects. Put anotherway, at any point in space time the equivalence principle guarantees theexistence of a local inertial frame, and an accelerometer measures theacceleration relative to that frame.[1] Such accelerations are popularlymeasured in terms of g-force. Single- and multi-axis models ofaccelerometer are available to detect magnitude and direction of theproper acceleration (or g-force), as a vector quantity, and can be usedto sense orientation (because direction of weight changes), coordinateacceleration (so long as it produces g-force or a change in g-force),vibration, shock, and falling in a resistive medium (a case where theproper acceleration changes, since it starts at zero, then increases).Micro-machined accelerometers are increasingly present in portableelectronic devices and video game controllers, to detect the position ofthe device or provide for game input. Pairs of accelerometers extendedover a region of space can be used to detect differences (gradients) inthe proper accelerations of frames of references associated with thosepoints. These devices are called gravity gradiometers, as they measuregradients in the gravitational field. Such pairs of accelerometers intheory may also be able to detect gravitational waves.

For purposes of the present invention, the term “active” refers to anindividual who is wearing a dosimeter or other type of sensor.

For purposes of the present invention, the term “active time period”refers to the time period that a person is active.

For the purposes of the present invention, the term “angle of incidence”refers to the angle between the direction of the radiation source and aline perpendicular (normal) to the detector surface.

For purposes of the present invention, the term “associated” withrespect to data refers to data that are associated or linked to eachother. For example, data relating the identity of an individual(identity data) wearing an integrated sensor module may be associatedwith the motion data for the individual obtained from an accelerometeror, optionally, from a gyroscope or, optionally, from the amplitude ofthe power signal from an energy harvester.

For the purposes of the present invention, the term “autonomous mobilesensor (AMS) network” refers a network of independently functioningmobile sensors, each capable of moving in response to the intensity ofthe detected event and their proximity to the other mobile sensors, suchthat the group of mobile sensors automatically follows the dynamicdistribution of the tracked entity as the intensity changes over time ordistributes over a geographic region or within a building or structure.

For the purposes of the present invention, the term “ANT” or “ANT+:refers to a proprietary wireless sensor network technology featuring awireless communications protocol stack that enables semiconductor radiosoperating in the 2.4 GHz industrial, scientific, and medical allocationof the RF spectrum (“ISM band”) to communicate by establishing standardrules for co-existence, data representation, signaling, authentication,and error detection. ANT is characterized by a low computationaloverhead and low to medium efficiency, resulting in low powerconsumption by the radios supporting the protocol.

For the purposes of the present invention, the term “Bluetooth®” refersto a wireless technology standard for exchanging data over shortdistances (using short-wavelength radio transmissions in the ISM bandfrom 2400-2480 MHz) from fixed and mobile devices, creating personalarea networks (PANs) with high levels of security. Created by telecomvendor Ericsson in 1994, it was originally conceived as a wirelessalternative to RS-232 data cables. It can connect several devices,overcoming problems of synchronization. Bluetooth® is managed by theBluetooth® Special Interest Group, which has more than 18,000 membercompanies in the areas of telecommunication, computing, networking, andconsumer electronics. Bluetooth® was standardized as IEEE 802.15.1, butthe standard is no longer maintained. The SIG oversees the developmentof the specification, manages the qualification program, and protectsthe trademarks. To be marketed as a Bluetooth® device, it must bequalified to standards defined by the SIG. A network of patents isrequired to implement the technology and are licensed only for thosequalifying devices.

For the purposes of the present invention, the term a “chemical sensor”refers to a device that measures the presence, concentration or absolutequantity of a given chemical entity, such as an element or molecule, ineither a gas, liquid or solid phase.

For the purposes of the present invention, the term “cloud computing” issynonymous with computing performed by computers that are locatedremotely and accessed via the Internet (the “Cloud”). It is a style ofcomputing where the computing resources are provided “as a service”,allowing users to access technology-enabled services “in the cloud”without knowledge of, expertise with, or control over the technologyinfrastructure that supports them. According to the IEEE ComputerSociety it “is a paradigm in which information is permanently stored inservers on the Internet and cached temporarily on clients that includedesktops, entertainment centers, table computers, notebooks, wallcomputers, handhelds, etc.” Cloud computing is a general concept thatincorporates virtualized storage, computing and web services and, often,software as a service (SaaS), where the common theme is reliance on theInternet for satisfying the computing needs of the users. For example,Google Apps provides common business applications online that areaccessed from a web browser, while the software and data are stored onthe servers. Some successful cloud architectures may have little or noestablished infrastructure or billing systems whatsoever includingPeer-to-peer networks like BitTorrent and Skype and volunteer computinglike SETI@home. The majority of cloud computing infrastructure currentlyconsists of reliable services delivered through next-generation datacenters that are built on computer and storage virtualizationtechnologies. The services may be accessible anywhere in the world, withthe Cloud appearing as a single point of access for all the computingneeds of data consumers. Commercial offerings may need to meet thequality of service requirements of customers and may offer service levelagreements. Open standards and open source software are also critical tothe growth of cloud computing. As customers generally do not own theinfrastructure, they are merely accessing or renting, they may foregocapital expenditure and consume resources as a service, paying insteadfor what they use. Many cloud computing offerings have adopted theutility computing model which is analogous to how traditional utilitieslike electricity are consumed, while others are billed on a subscriptionbasis. By sharing “perishable and intangible” computing power betweenmultiple tenants, utilization rates may be improved (as servers are notleft idle) which can reduce costs significantly while increasing thespeed of application development. A side effect of this approach is that“computer capacity rises dramatically” as customers may not have toengineer for peak loads. Adoption has been enabled by “increasedhigh-speed bandwidth” which makes it possible to receive the sameresponse times from centralized infrastructure at other sites.

For purposes of the present invention, the term “computer” refers to anytype of computer or other device that implements software including anindividual computer such as a personal computer, laptop computer, tabletcomputer, mainframe computer, mini-computer, etc. A computer also refersto electronic devices such as an electronic scientific instrument suchas a server, spectrometer, a smartphone, an eBook reader, a cell phone,a television, a handheld electronic game console, a videogame console, acompressed audio or video player such as an MP3 player, a Blu-rayplayer, a DVD player, etc. In addition, the term “computer” refers toany type of network of computers, such as a network of computers in abusiness, a computer bank, the Cloud, the Internet, etc. Variousprocesses of the present invention may be carried out using a computer.Various functions of the present invention may be performed by one ormore computers.

For the purposes of the present invention, the term “computer hardware”is the digital circuitry and physical devices of a computer system, asopposed to computer software, which is stored on a hardware device suchas a hard disk. Most computer hardware is not seen by normal users,because it is embedded within a variety of every day systems, such as inautomobiles, microwave ovens, electrocardiograph machines, compact discplayers, and video games, among many others. A typical personal computerconsists of a case or chassis in a tower shape (desktop) and thefollowing parts: motherboard, CPU, RAM, firmware, internal buses (PIC,PCI-E, USB, HyperTransport, CSI, AGP, VLB), external bus controllers(parallel port, serial port, USB, Firewire, SCSI. PS/2, ISA, EISA, MCA),power supply, case control with cooling fan, storage controllers(CD-ROM, DVD, DVD-ROM, DVD Writer, DVD RAM Drive, Blu-ray, BD-ROM, BDWriter, floppy disk, USB Flash, tape drives, SATA, SAS), videocontroller, sound card, network controllers (modem, NIC), andperipherals, including mice, keyboards, pointing devices, gamingdevices, scanner, webcam, audio devices, printers, monitors, etc.

For the purposes of the present invention, the term “computer network”refers to a group of interconnected computers. Networks may beclassified according to a wide variety of characteristics. The mostcommon types of computer networks in order of scale include: PersonalArea Network (PAN), Local Area Network (LAN), Campus Area Network (CAN),Metropolitan Area Network (MAN), Wide Area Network (WAN), Global AreaNetwork (GAN), Internetwork (intranet, extranet, Internet), and varioustypes of wireless networks. All networks are made up of basic hardwarebuilding blocks to interconnect network nodes, such as Network InterfaceCards (NICs), Bridges, Hubs, Switches, and Routers. In addition, somemethod of connecting these building blocks is required, usually in theform of galvanic cable (most commonly category 5 cable). Less common aremicrowave links (as in IEEE 802.11) or optical cable (“optical fiber”).

For the purposes of the present invention, the term “computer software”refers to a general term used to describe a collection of computerprograms, procedures and documentation that perform some tasks on acomputer system. The term includes application software such as wordprocessors which perform productive tasks for users, system softwaresuch as operating systems, which interface with hardware to provide thenecessary services for application software, and middleware whichcontrols and co-ordinates distributed systems. Software may includewebsites, programs, video games, etc. that are coded by programminglanguages like C, C++, Java, etc. Computer software is usually regardedas anything but hardware, meaning the “hard” are the parts that aretangible (able to hold) while the “soft” part is the intangible objectsinside the computer. Computer software is so called to distinguish itfrom computer hardware, which encompasses the physical interconnectionsand devices required to store and execute (or run) the software. At thelowest level, software consists of a machine language specific to anindividual processor. A machine language consists of groups of binaryvalues signifying processor instructions which change the state of thecomputer from its preceding state.

For the purposes of the present invention, the term “computer system”refers to any type of computer system that implements software includingan individual computer such as a personal computer, mainframe computer,mini-computer, etc. In addition, computer system refers to any type ofnetwork of computers, such as a network of computers in a business, theInternet, personal data assistant (PDA), devices such as a cell phone, atelevision, a videogame console, a compressed audio or video player suchas an MP3 player, a DVD player, a microwave oven, etc. A personalcomputer is one type of computer system that typically includes thefollowing components: a case or chassis in a tower shape (desktop) andthe following parts: motherboard, CPU, RAM, firmware, internal buses(PIC, PCI-E, USB, HyperTransport, CSI, AGP, VLB), external buscontrollers (parallel port, serial port, USB, Firewire, SCSI. PS/2, ISA,EISA, MCA), power supply, case control with cooling fan, storagecontrollers (CD-ROM, DVD, DVD-ROM, DVD Writer, DVD RAM Drive, Blu-ray,BD-ROM, BD Writer, floppy disk, USB Flash, tape drives, SATA, SAS),video controller, sound card, network controllers (modem, NIC), andperipherals, including mice, keyboards, pointing devices, gamingdevices, scanner, webcam, audio devices, printers, monitors, etc.

For the purposes of the present invention, the term “data” means thereinterpretable representation of information in a formalized mannersuitable for communication, interpretation, or processing. Although onetype of common type data is a computer file, data may also be streamingdata, a web service, etc. The term “data” is used to refer to one ormore pieces of data.

For the purposes of the present invention, the term “database” or “datarecord” refers to a structured collection of records or data that isstored in a computer system. The structure is achieved by organizing thedata according to a database model. The model in most common use todayis the relational model. Other models such as the hierarchical model andthe network model use a more explicit representation of relationships(see below for explanation of the various database models). A computerdatabase relies upon software to organize the storage of data. Thissoftware is known as a database management system (DBMS). Databasemanagement systems are categorized according to the database model thatthey support. The model tends to determine the query languages that areavailable to access the database. A great deal of the internalengineering of a DBMS, however, is independent of the data model, and isconcerned with managing factors such as performance, concurrency,integrity, and recovery from hardware failures. In these areas there arelarge differences between products.

For the purposes of the present invention, the term “database managementsystem (DBMS)” represents computer software designed for the purpose ofmanaging databases based on a variety of data models. A DBMS is a set ofsoftware programs that controls the organization, storage, management,and retrieval of data in a database. DBMS are categorized according totheir data structures or types. It is a set of prewritten programs thatare used to store, update and retrieve a Database.

For the purposes of the present invention, the term “data storagemedium” or “data storage device” refers to any medium or media on whicha data may be stored for use by a computer system. Examples of datastorage media include floppy disks, Zip™ disks, CD-ROM, CD-R, CD-RW,DVD, DVD-R, memory sticks, flash memory, hard disks, solid state disks,optical disks, etc. Two or more data storage media acting similarly to asingle data storage medium may be referred to as a “data storage medium”for the purposes of the present invention. A data storage medium may bepart of a computer.

For the purposes of the present invention, the term “dosimeter” refersto a device for measuring an individual's or an object's exposure tosomething in the environment—particularly to a hazard inflictingcumulative impact over long periods of time, or over a lifetime. Aradiation dosimeter measures exposure to ionizing radiation. Theradiation dosimeter is of fundamental importance in the disciplines ofradiation dosimetry and health physics. Other types of dosimeters aresound dosimeters, ultraviolet dosimeters and electromagnetic fielddosimeters. Ionizing radiation, such as X-rays, alpha rays, beta rays,and gamma rays, are undetectable by the human senses, therefore ameasuring device, such as a dosimeter, is used to detect, measure andrecord this, and in some cases give an alarm when a preset level isexceeded. Ionizing radiation damage to the body is cumulative, and isrelated to the total dose received, for which the SI unit is thesievert. Therefore, workers exposed to radiation, such as radiographers,nuclear power plant workers, doctors, physicists and radiationtherapists employing radiotherapy machines, those in laboratories usingradionuclides, and some HAZMAT teams are required to wear dosimeters sotheir employers can keep a record of their exposure to verify that it isbelow legally prescribed limits Such devices may be recognized as “legaldosimeters,” meaning that they have been approved for use in recordingpersonnel dose for regulatory purposes.

For the purposes of the present invention, the term “energy compensatingmaterial” refers to a material that when placed between an OSLM and asource of gamma radiation or x-ray radiation alters the response over arange of gamma energies or x-ray energies compared to the OSLM exposedwith no compensating or filtering material. Examples of energycompensating materials are copper and aluminum.

For the purposes of the present invention, the term “flocking-algorithm”refers to an computational procedure that allows a network of mobilesensors to move as a function of each sensor's proximity to other mobilesensors as well as the intensity or amplitude of a measured event, suchthat the network of mobile sensors moves autonomously in a concerted,self-organized fashion that tracks the dynamic motion and distributionof the measured event.

For purposes of the present invention, the term “hardware and/orsoftware” refers to functions that may be performed by computersoftware, computer hardware, or a combination of both computer hardwareand computer software. Various features of the present invention may beperformed by hardware and/or software.

For purposes of the present invention, the term “individual” refers toan individual mammal, such as a human being.

For the purposes of the present invention, the term “Internet” is aglobal system of interconnected computer networks that interchange databy packet switching using the standardized Internet Protocol Suite(TCP/IP). It is a “network of networks” that consists of millions ofprivate and public, academic, business, and government networks of localto global scope that are linked by copper wires, fiber-optic cables,wireless connections, and other technologies. The Internet carriesvarious information resources and services, such as electronic mail,online chat, file transfer and file sharing, online gaming, and theinter-linked hypertext documents and other resources of the World WideWeb (WWW).

For the purposes of the present invention, the term “Internet protocol(IP)” refers to a protocol used for communicating data across apacket-switched internetwork using the Internet Protocol Suite (TCP/IP).IP is the primary protocol in the Internet Layer of the InternetProtocol Suite and has the task of delivering datagrams (packets) fromthe source host to the destination host solely based on its address. Forthis purpose the Internet Protocol defines addressing methods andstructures for datagram encapsulation. The first major version ofaddressing structure, now referred to as Internet Protocol Version 4(Ipv4) is still the dominant protocol of the Internet, although thesuccessor, Internet Protocol Version 6 (Ipv6) is actively deployedworld-wide. In one embodiment, an EGI-SOA of the present invention maybe specifically designed to seamlessly implement both of theseprotocols.

For the purposes of the present invention, the term “intranet” refers toa set of networks, using the Internet Protocol and IP-based tools suchas web browsers and file transfer applications that are under thecontrol of a single administrative entity. That administrative entitycloses the intranet to all but specific, authorized users. Mostcommonly, an intranet is the internal network of an organization. Alarge intranet will typically have at least one web server to provideusers with organizational information. Intranets may or may not haveconnections to the Internet. If connected to the Internet, the intranetis normally protected from being accessed from the Internet withoutproper authorization. The Internet is not considered to be a part of theintranet.

For the purposes of the present invention, the term “ionizing radiation”refers to any particulate or electromagnetic radiation that is capableof dissociating atoms into a positively and negatively charged ion pair.The present invention may be used to determine doses of both directlyionizing radiation and indirectly ionizing radiation. Ionizing (orionising) radiation is radiation composed of particles that individuallycarry enough kinetic energy to liberate an electron from an atom ormolecule, ionizing it. Ionizing radiation is generated through nuclearreactions, either artificial or natural, by very high temperature (e.g.,plasma discharge or the corona of the Sun), via production of highenergy particles in particle accelerators, or due to acceleration ofcharged particles by the electromagnetic fields produced by naturalprocesses, from lightning to supernova explosions. When ionizingradiation is emitted by or absorbed by an atom, it can liberate anatomic particle (typically an electron, proton, or neutron, butsometimes an entire nucleus) from the atom. Such an event can alterchemical bonds and produce ions, usually in ion-pairs, that areespecially chemically reactive. This greatly magnifies the chemical andbiological damage per unit energy of radiation because chemical bondswill be broken in this process. If the atom was inside a crystal latticein a solid phase, then a “hole” will exist where the original atom was.Ionizing radiation includes cosmic rays, Alpha particles, Betaparticles, Gamma rays, X-rays, and in general any charged particlemoving at relativistic speeds. Neutrons are considered ionizingradiation at any speed. Ionizing radiation includes some portion of theultraviolet spectrum, depending on context. Radio waves, microwaves,infrared light, and visible light are normally considered non-ionizingradiation, although very high intensity beams of these radiations canproduce sufficient heat to exhibit some similar properties to ionizingradiation, by altering chemical bonds and removing electrons from atoms.Ionizing radiation is ubiquitous in the environment, and comes fromnaturally occurring radioactive materials and cosmic rays. Commonartificial sources are artificially produced radioisotopes, X-ray tubesand particle accelerators. Ionizing radiation is invisible and notdirectly detectable by human senses, so instruments such as Geigercounters are usually required to detect its presence. In some cases itmay lead to secondary emission of visible light upon interaction withmatter, such as in Cherenkov radiation and radioluminescence. It hasmany practical uses in medicine, research, construction, and otherareas, but presents a health hazard if used improperly. Exposure toionizing radiation causes damage to living tissue, and can result inmutation, radiation sickness, cancer, and death.

For the purposes of the present invention, the term “ionizing radiationsensor” refers to a device that measures the presence or activity of amaterial or substance that emits or generates ionizing radiation.

For the purposes of the present invention, the term “irradiation” refersto the conventional meaning of the term “irradiation”, i.e., exposure tohigh energy charge particles, e.g., electrons, protons, alpha particles,etc., or electromagnetic radiation of wave-lengths shorter than those ofvisible light, e.g., gamma rays, x-rays, ultraviolet, etc.

For purposes of the present invention, the term “linked type of motion”refers to one type of motion causing a second type of motion. Forexample, a walking motion by an individual is one type of motion and maycause a linked second type of motion, i.e., a pendulum motion of anyindividual's wrist. A running motion by an individual is also one typeof motion and may cause a second linked type of motion, i.e., a cyclicmotion at the individual's wrist later to a direction detected by amotion sensor.

For the purposes of the present invention, the term “local area network(LAN)” refers to a network covering a small geographic area, like ahome, office, or building. Current LANs are most likely to be based onEthernet technology. The cables to the servers are typically on Cat 5eenhanced cable, which will support IEEE 802.3 at 1 Gbit/s. A wirelessLAN may exist using a different IEEE protocol, 802.11b, 802.11g orpossibly 802.11n. The defining characteristics of LANs, in contrast toWANs (wide area networks), include their higher data transfer rates,smaller geographic range, and lack of a need for leasedtelecommunication lines. Current Ethernet or other IEEE 802.3 LANtechnologies operate at speeds up to 10 Gbit/s.

For purposes of the present invention, the term “location data” and theterm “position data” refer to data about the location of an individualor an object, such as a dosimeter. Location data may be generated usinga position beacon, a GPS device, etc.

For the purposes of the current invention, the term “low poweredwireless network” refers to an ultra-low powered wireless networkbetween sensor nodes and a centralized device. The ultra-low power isneeded by devices that need to operate for extended periods of time fromsmall batteries energy scavenging technology. Examples of low poweredwireless networks are ANT, ANT+, Bluetooth Low Energy (BLE), ZigBee andWiFi.

For purposes of the present invention, the term “machine-readablemedium” refers to any tangible or non-transitory medium that is capableof storing, encoding or carrying instructions for execution by themachine and that cause the machine to perform any one or more of themethodologies of the present invention, or that is capable of storing,encoding or carrying data structures utilized by or associated with suchinstructions. The term “machine-readable medium” includes, but islimited to, solid-state memories, and optical and magnetic media.Specific examples of machine-readable media include non-volatile memory,including by way of example, semiconductor memory devices, e.g., EPROM,EEPROM, and flash memory devices; magnetic disks such as internal harddisks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROMdisks. The term “machine-readable medium” may include a single medium ormultiple media (e.g., a centralized or distributed database, and/orassociated caches and servers) that store the one or more instructionsor data structures. A machine-readable medium may be part of a computer.

For the purposes of the present invention, the term “MEMS” refers toMicro-Electro-Mechanical Systems. MEMS, is a technology that in its mostgeneral form may be defined as miniaturized mechanical andelectro-mechanical elements (i.e., devices and structures) that are madeusing the techniques of microfabrication. The critical physicaldimensions of MEMS devices can vary from well below one micron on thelower end of the dimensional spectrum, all the way to severalmillimeters. Likewise, the types of MEMS devices can vary fromrelatively simple structures having no moving elements, to extremelycomplex electromechanical systems with multiple moving elements underthe control of integrated microelectronics. A main criterion of MEMS mayinclude that there are at least some elements having some sort ofmechanical functionality whether or not these elements can move. Theterm used to define MEMS varies in different parts of the world. In theUnited States they are predominantly called MEMS, while in some otherparts of the world they are called “Microsystems Technology” or“micromachined devices.” While the functional elements of MEMS areminiaturized structures, sensors, actuators, and microelectronics, mostnotable elements may include microsensors and microactuators.Microsensors and microactuators may be appropriately categorized as“transducers,” which are defined as devices that convert energy from oneform to another. In the case of microsensors, the device typicallyconverts a measured mechanical signal into an electrical signal.

For the purposes of the present invention the term “mesh networking”refers to a type of networking where each node must not only capture anddisseminate its own data, but also serve as a relay for other nodes,that is, it must collaborate to propagate the data in the network. Amesh network can be designed using a flooding technique or a routingtechnique. When using a routing technique, the message is propagatedalong a path, by hopping from node to node until the destination isreached. To ensure all its paths' availability, a routing network mustallow for continuous connections and reconfiguration around broken orblocked paths, using self-healing algorithms. A mesh network whose nodesare all connected to each other is a fully connected network. Meshnetworks can be seen as one type of ad hoc network. Mobile ad hocnetworks and mesh networks are therefore closely related, but mobile adhoc networks also have to deal with the problems introduced by themobility of the nodes. The self-healing capability enables a routingbased network to operate when one node breaks down or a connection goesbad. As a result, the network is typically quite reliable, as there isoften more than one path between a source and a destination in thenetwork. Although mostly used in wireless situations, this concept isalso applicable to wired networks and software interaction.

For the purposes of the present invention the term “microfluidics”refers to a branch micro-fabrication which is concerned with developingmeans of handling small volumes of liquids. An aspect of the presentinvention is to utilize fluidic structures consisting of a large numberof microscopic volumes of liquids (e.g., volumes from picoliters tomicroliters) as a working element in a mechanical-to electrical energyconversion system. The large number of these microscopic elements (onthe order of hundreds or even thousands) yields a realistic amount ofelectrical energy that can be generated from a relatively small volumeof mechanical motion.

For the purposes of the present invention the term “mobile ad hocnetwork” is a self-configuring infrastructureless network of mobiledevices connected by wireless. Ad hoc is Latin and means “for thispurpose”. Each device in a mobile ad hoc network is free to moveindependently in any direction, and will therefore change its links toother devices frequently. Each must forward traffic unrelated to its ownuse, and therefore be a router. The primary challenge in building amobile ad hoc network is equipping each device to continuously maintainthe information required to properly route traffic. Such networks mayoperate by themselves or may be connected to the larger Internet. Mobilead hoc networks are a kind of wireless ad hoc networks that usually hasa routable networking environment on top of a Link Layer ad hoc network.The growths of laptops and wireless networks have made mobile ad hocnetworks a popular research topic since the mid-1990s. Many academicpapers evaluate protocols and their abilities, assuming varying degreesof mobility within a bounded space, usually with all nodes within a fewhops of each other. Different protocols are then evaluated based onmeasure such as the packet drop rate, the overhead introduced by therouting protocol, end-to-end packet delays, network throughput etc.

For purposes of the present invention, the term “motion data” and theterm “motion activity data” refer to data relating to the motion of anindividual, an object or a device and to the motion of any part of anindividual, an object or a device. Motion data may have associated timedata relating to when motion started, when motion stopped, the durationof motion, etc.

For the purposes of the present invention, the term “network hub” refersto an electronic device that contains multiple ports. When a packetarrives at one port, it is copied to all the ports of the hub fortransmission. When the packets are copied, the destination address inthe frame does not change to a broadcast address. It does this in arudimentary way, it simply copies the data to all of the Nodes connectedto the hub. This term is also known as hub. The term “Ethernet hub,”“active hub,” “network hub,” “repeater hub,” “multiport repeater” or“hub” may also refer to a device for connecting multiple Ethernetdevices together and making them act as a single network segment. It hasmultiple input/output (I/O) ports, in which a signal introduced at theinput of any port appears at the output of every port except theoriginal incoming. A hub works at the physical layer (layer 1) of theOSI model. The device is a form of multiport repeater. Repeater hubsalso participate in collision detection, forwarding a jam signal to allports if it detects a collision.

For purposes of the present invention, the term “on-board” refers to acomponent, such as a motion sensor, GPS device, etc. that is on the sameprinted circuit board as one or more radiation sensors of an integratedsensor module of the present invention.

For purposes of the present invention, the term “processor” refers to adevice that performs the basic operations in a computer. Amicroprocessor is one example of a processor.

For the purposes of the present invention, the term “radiationattenuating material” refers to a material that reduces the intensity ofincident radiation by absorbing some or all of the energy of theradiation within the material.

For purposes of the present invention, the term “radiation dosage data”refers to data based on the exposure of a radiation dosimeter to one ordoses of radiation. Time data may be associated with radiation dosagedata. For example, a time period when the radiation dosimeter is exposedto one or more doses of radiation.

For the purposes of the present invention, the term “radiationdosimetry” refers to the conventional meaning of the term “radiationdosimetry”, i.e., the measurement of the amount of radiation doseabsorbed in a material, an object or the body of an individual.

For the purposes of the present invention, the term “radiation sensingmaterial” refers to a material used to sense radiation in a radiationsensor. Examples of radiation sensitive materials including opticallystimulated luminescent materials for OSL sensors, thermoluminescentmaterials for thermoluminescent dosimetry (TLD) sensors, etc.

For the purposes of the present invention, the term “random-accessmemory (RAM)” refers to a type of computer data storage. Today it takesthe form of integrated circuits that allow the stored data to beaccessed in any order, i.e. at random. The word random thus refers tothe fact that any piece of data can be returned in a constant time,regardless of its physical location and whether or not it is related tothe previous piece of data. This contrasts with storage mechanisms suchas tapes, magnetic discs and optical discs, which rely on the physicalmovement of the recording medium or a reading head. In these devices,the movement takes longer than the data transfer, and the retrieval timevaries depending on the physical location of the next item. The word RAMis mostly associated with volatile types of memory (such as DRAM memorymodules), where the information is lost after the power is switched off.However, many other types of memory are RAM as well, including mosttypes of ROM and a kind of flash memory called NOR-Flash.

For the purposes of the present invention, the term “read-only memory(ROM)” refers to a class of storage media used in computers and otherelectronic devices. Because data stored in ROM cannot be modified (atleast not very quickly or easily), it is mainly used to distributefirmware (software that is very closely tied to specific hardware, andunlikely to require frequent updates). In its strictest sense, ROMrefers only to mask ROM (the oldest type of solid state ROM), which isfabricated with the desired data permanently stored in it, and thus cannever be modified. However, more modern types such as EPROM and flashEEPROM can be erased and re-programmed multiple times; they are stilldescribed as “read-only memory” because the reprogramming process isgenerally infrequent, comparatively slow, and often does not permitrandom access writes to individual memory locations.

For the purposes of the present invention, the term “real-timeprocessing” refers to a processing system designed to handle workloadswhose state is constantly changing. Real-time processing means that atransaction is processed fast enough for the result to come back and beacted on as transaction events are generated. In the context of adatabase, real-time databases are databases that are capable of yieldingreliable responses in real-time.

For the purposes of the present invention, the term “router” refers to anetworking device that forwards data packets between networks usingheaders and forwarding tables to determine the best path to forward thepackets. Routers work at the network layer of the TCP/IP model or layer3 of the OSI model. Routers also provide interconnectivity between likeand unlike media devices. A router is connected to at least twonetworks, commonly two LANs or WANs or a LAN and its ISP's network.

For the purposes of the present invention, the term “sensor” refers to acollector and/or producer of information and/or data. A sensor can be aninstrument or a living organism (e.g. a person). For example, a sensormay be a position locating sensor such as a GPS device, a thermometer, amobile phone, an individual writing a report, etc. A sensor is an entitycapable of observing a phenomenon and returning an observed value. Forexample, a mercury thermometer converts the measured temperature intoexpansion and contraction of a liquid which can be read on a calibratedglass tube. A thermocouple converts temperature to an output voltagewhich can be read by a voltmeter. For accuracy, all sensors are often becalibrated against known standards. A sensor may include a device whichdetects or measures a physical property and records, indicates, orresponds to that physical property.

For the purposes of the present invention, the term “server” refers to asystem (software and suitable computer hardware) that responds torequests across a computer network to provide, or help to provide, anetwork service. Servers can be run on a dedicated computer, which isalso often referred to as “the server,” but many networked computers arecapable of hosting servers. In many cases, a computer can provideseveral services and have several servers running. Servers may operatewithin a client-server architecture and may comprise computer programsrunning to serve the requests of other programs—the clients. Thus, theserver may perform some task on behalf of clients. The clients typicallyconnect to the server through the network but may run on the samecomputer. In the context of Internet Protocol (IP) networking, a serveris a program that operates as a socket listener. Servers often provideessential services across a network, either to private users inside alarge organization or to public users via the Internet. Typicalcomputing servers are database server, file server, mail server, printserver, web server, gaming server, application server, or some otherkind of server. Numerous systems use this client/server networking modelincluding Web sites and email services. An alternative model,peer-to-peer networking may enable all computers to act as either aserver or client as needed.

For the purposes of the present invention, the term “solid-stateelectronics” refers to those circuits or devices built entirely fromsolid materials and in which the electrons, or other charge carriers,are confined entirely within the solid material. The term is often usedto contrast with the earlier technologies of vacuum and gas-dischargetube devices and it is also conventional to exclude electro-mechanicaldevices (relays, switches, hard drives and other devices with movingparts) from the term solid state. While solid-state can includecrystalline, polycrystalline and amorphous solids and refer toelectrical conductors, insulators and semiconductors, the buildingmaterial is most often a crystalline semiconductor. Common solid-statedevices include transistors, microprocessor chips, and RAM. Aspecialized type of RAM called flash RAM is used in flash drives andmore recently, solid state drives to replace mechanically rotatingmagnetic disc hard drives. More recently, the integrated circuit (IC),the light-emitting diode (LED), and the liquid-crystal display (LCD)have evolved as further examples of solid-state devices. In asolid-state component, the current is confined to solid elements andcompounds engineered specifically to switch and amplify it.

For the purposes of the present invention, the term “solid state sensor”refers to sensor built entirely from a solid-phase material such thatthe electrons or other charge carriers produced in response to themeasured quantity stay entirely with the solid volume of the detector,as opposed to gas-discharge or electro-mechanical sensors. Puresolid-state sensors have no mobile parts and are distinct fromelectro-mechanical transducers or actuators in which mechanical motionis created proportional to the measured quantity.

For purposes of the present invention, the term the term “storagemedium” refers to any form of storage that may be used to store bits ofinformation. Examples of storage include both volatile and non-volatilememories such as MRRAM, MRRAM, ERAM, flash memory, RFID tags, floppydisks, Zip™ disks, CD-ROM, CD-R, CD-RW, DVD, DVD-R, flash memory, harddisks, optical disks, etc. Two or more storage media acting similarly toa single data storage medium may be referred to as a “storage medium”for the purposes of the present invention. A storage medium may be partof a computer.

For the purposes of the present invention, the term “transmissioncontrol protocol (TCP)” refers to one of the core protocols of theInternet Protocol Suite. TCP is so central that the entire suite isoften referred to as “TCP/IP.” Whereas IP handles lower-leveltransmissions from computer to computer as a message makes its wayacross the Internet, TCP operates at a higher level, concerned only withthe two end systems, for example a Web browser and a Web server. Inparticular, TCP provides reliable, ordered delivery of a stream of bytesfrom one program on one computer to another program on another computer.Besides the Web, other common applications of TCP include e-mail andfile transfer. Among its management tasks, TCP controls message size,the rate at which messages are exchanged, and network trafficcongestion.

For the purposes of the present invention, the term “time” refers to acomponent of a measuring system used to sequence events, to compare thedurations of events and the intervals between them, and to quantify themotions of objects. Time is considered one of the few fundamentalquantities and is used to define quantities such as velocity. Anoperational definition of time, wherein one says that observing acertain number of repetitions of one or another standard cyclical event(such as the passage of a free-swinging pendulum) constitutes onestandard unit such as the second, has a high utility value in theconduct of both advanced experiments and everyday affairs of life.Temporal measurement has occupied scientists and technologists, and wasa prime motivation in navigation and astronomy. Periodic events andperiodic motion have long served as standards for units of time.Examples include the apparent motion of the sun across the sky, thephases of the moon, the swing of a pendulum, and the beat of a heart.Currently, the international unit of time, the second, is defined interms of radiation emitted by cesium atoms.

For purposes of the present invention, the term “time data” refers todata relating to time. Time data may be associated with other types ofdata, such as motion data. For example, motion data may have associatedtime data relating to when motion started, when motion stopped, theduration of motion, etc. Time data may be generated in a number of waysin the present invention. For example, time data may be generated by: aclock that is part of a radiation sensor device, a hardware or softwareclock that is part of a processor that is part of the radiation sensordevice, a hardware or software clock that is part of a computer thatprocesses data from the radiation sensor, etc.

For the purposes of the present invention, the term “timestamp” refersto a sequence of characters, denoting the date and/or time at which acertain event occurred. This data is usually presented in a consistentformat, allowing for easy comparison of two different records andtracking progress over time; the practice of recording timestamps in aconsistent manner along with the actual data is called timestamping.Timestamps are typically used for logging events, in which case eachevent in a log is marked with a timestamp. In file systems, timestampmay mean the stored date/time of creation or modification of a file. TheInternational Organization for Standardization (ISO) has defined ISO8601 which standardizes timestamps.

For purposes of the present invention, the term “type of motion” refersto a type of motion by all or part of the body of an individual. Forexample, a walking motion by an individual is one type of motion and maycause a second type of motion, i.e., a pendulum motion of anyindividual's wrist. A running motion by an individual is also one typeof motion and may cause a second type of motion, i.e., a cyclic motionat the individual's wrist later to a direction detected by one or moremotion sensors. The motion of a motorized vehicle is another type ofmotion and may cause secondary and tertiary types of motion, i.e., theforward motion of the vehicle, the vibratory oscillation of the vehicleand the individual in the vehicle, and the periodic motion of theindividual's body during the normal course of operating the vehicle. Alack of motion is also considered as one type of motion and may be due,for example, to removing the dosimeter from the individual participantand placing it in a desk, on a table top, or on a fixed structuredesigned to act as a holder for the dosimeter.

For the purposes of the present invention, the term “visual displaydevice” or “visual display apparatus” includes any type of visualdisplay device or apparatus such as a CRT monitor, LCD screen, LEDs, aprojected display, a printer for printing out an image such as a pictureand/or text, etc. A visual display device may be a part of anotherdevice such as a computer monitor, television, projector, telephone,cell phone, smartphone, laptop computer, tablet computer, handheld musicand/or video player, personal data assistant (PDA), handheld gameplayer, head mounted display, a heads-up display (HUD), a globalpositioning system (GPS) receiver, automotive navigation system,dashboard, watch, microwave oven, electronic organ, automatic tellermachine (ATM) etc.

For the purposes of the present invention, the term “web service” refersto the term defined by the W3C as “a software system designed to supportinteroperable machine-to-machine interaction over a network”. Webservices are frequently just web APIs that can be accessed over anetwork, such as the Internet, and executed on a remote system hostingthe requested services. The W3C Web service definition encompasses manydifferent systems, but in common usage the term refers to clients andservers that communicate using XML messages that follow the SOAPstandard. In such systems, there is often machine-readable descriptionof the operations offered by the service written in the Web ServicesDescription Language (WSDL). The latter is not a requirement of a SOAPendpoint, but it is a prerequisite for automated client-side codegeneration in many Java and .NET SOAP frameworks. Some industryorganizations, such as the WS-I, mandate both SOAP and WSDL in theirdefinition of a Web service. More recently, RESTful Web services havebeen used to better integrate with HTTP compared to SOAP-based services.They do not require XML messages or WSDL service-API definitions.

For the purposes of the present invention, the term “wide area network(WAN)” refers to a data communications network that covers a relativelybroad geographic area (i.e. one city to another and one country toanother country) and that often uses transmission facilities provided bycommon carriers, such as telephone companies. WAN technologies generallyfunction at the lower three layers of the OSI reference model: thephysical layer, the data link layer, and the network layer.

For purposes of the present invention, the term “designated work period”refers to a period of time that a person is scheduled to be at work.

For the purposes of the present invention, the term “World Wide WebConsortium (W3C)” refers to the main international standardsorganization for the World Wide Web (abbreviated WWW or W3). It isarranged as a consortium where member organizations maintain full-timestaff for the purpose of working together in the development ofstandards for the World Wide Web. W3C also engages in education andoutreach, develops software and serves as an open forum for discussionabout the Web. W3C standards include: CSS, CGI, DOM, GRDDL, HTML, OWL,RDF, SVG, SISR, SOAP, SMIL, SRGS, SSML, VoiceXML, XHTML+Voice, WSDL,XACML. XHTML, XML, XML Events, Xforms, XML Information, Set, XML Schema,Xpath, Xquery and XSLT.

For the purposes of the present invention, the term “ZigBee” refers aspecification for a suite of high level communication protocols used tocreate personal area networks built from small, low-power digitalradios. ZigBee is based on an IEEE 802 standard. Though low-powered,ZigBee devices often transmit data over longer distances by passing datathrough intermediate devices to reach more distant ones, creating a meshnetwork; i.e., a network with no centralized control or high-powertransmitter/receiver able to reach all of the networked devices. Thedecentralized nature of such wireless ad-hoc networks make them suitablefor applications where a central node can't be relied upon. ZigBee maybe used in applications that require a low data rate, long battery life,and secure networking. ZigBee has a defined rate of 250 kbit/s, bestsuited for periodic or intermittent data or a single signal transmissionfrom a sensor or input device. Applications include wireless lightswitches, electrical meters with in-home-displays, traffic managementsystems, and other consumer and industrial equipment that requiresshort-range wireless transfer of data at relatively low rates. Thetechnology defined by the ZigBee specification is intended to be simplerand less expensive than other WPANs, such as Bluetooth® or Wi-Fi. Zigbeenetworks are secured by 128 bit encryption keys.

Description

In existing passive, integrating radiation monitoring devices, such asfilm, TLD or OSL sensors, incident radiation is accumulated and storedwithin the molecular structure of the sensor without any need ofelectrical power. This characteristic makes passive sensors ideal forsituations where the risk of a power interruption is unacceptable.Multiple radiation sensors are generally mounted in a holder containingone or more filters that alter the amounts, energies and types ofradiation able to reach the sensors. These filters typically sandwichthe sensors to achieve correct assessments when the radiation enters thedosimeter from various angles of incidence. To analyze the sensors, theymust be removed from between the filters and the holder and physicallypresented to the processing system required to elicit the quantitativeattribute exhibited by the sensor following exposure to radiation.

Radiation dosimeters based on optically stimulated luminescence (OSL)utilize an optical path whereby a stimulating beam of light canilluminate the OSL sensor(s) and the resultant radiation inducedluminescence can be routed back through the same or alternate opticalpath to a light detector such as a photomultiplier tube that quantifiesthe amount of luminescent light. For more information on OSL materialsand systems, see, U.S. Pat. No. 5,731,590 issued to Miller; U.S. Pat.No. 6,846,434 issued to Akselrod; U.S. Pat. No. 6,198,108 issued toSchweitzer et al.; U.S. Pat. No. 6,127,685 issued to Yoder et al.; U.S.patent application Ser. No. 10/768,094 filed by Akselrod et al.; all ofwhich are incorporated herein by reference in their entireties. See alsoOptically Stimulated Luminescence Dosimetry, Lars Botter-Jensen et al.,Elesevier, 2003; Klemic, G., Bailey, P., Miller, K., Monetti, M.External radiation dosimetry in the aftermath of radiological terroristevent, Rad. Prot. Dosim., in press; Akselrod, M. S., Kortov, V. S., andGorelova, E. A., Preparation and properties of Al2O3:C, Radiat. Prot.Dosim. 47, 159-164 (1993); and Akselrod, M. S., Lucas, A. C., Polf, J.C., McKeever, S. W. S. Optically stimulated luminescence of Al2O3:C,Radiation Measurements, 29, (3-4), 391-399 (1998), all of which areincorporated herein by reference in their entireties.

Personnel dosimeters are expected to move relative to an exposure sourceduring working hours (the monitoring period) as the individual wearingthe dosimeter (the participant) moves during the normal course ofperforming the monitored activities. Dosimeters that remain stationaryor static for extended periods of time cannot be in use and, if thedosimeter should have been in use during a monitored period, then theparticipant is out of compliance.

Furthermore, if a dosimeter is exposed in the static state, then thatwould be an abnormal occupational exposure that might occur, forexample, if the participant was not. However, if a dosimeter is exposedduring normal motion, then that would provide evidence of a routine, asopposed to abnormal, occupational exposure.

In one embodiment, the present invention apparatus and system consistingof multiple sensor devices (including one or more passive, integratingelectronic radiation sensors, a MEMS accelerometer, a wirelesstransmitter and, optionally, a GPS or other positional or locationaldevice, a thermistor, or other chemical, biological or EMF sensors) andcomputer algorithms and programs for calculating the dose from the event(e.g., the personal dose equivalent), and for the simultaneous detectionand wireless transmission of ionizing radiation, motion and globalposition for use in occupational and environmental dosimetry. Thepresent invention is a new embodiment of existing sensors in a uniquenew product using new processes and algorithms to create aself-contained, passive, integrating dosimeter that constructs a uniquerecord of event intensity, location, time of the event, temperature andother specialized sensor data such as biological or chemicalmeasurements.

Accordingly, aspects of the disclosed invention provide the use of MEMSand nanotechnology manufacturing techniques to encapsulate individualionizing radiation sensor elements within a radiation attenuatingmaterial that provides a “filtration bubble” around the sensor element,the use of multiple attenuating materials (filters) around multiplesensor elements, and the use of a software algorithm to discriminatebetween different types of ionizing radiation and different radiationenergy.

In one embodiment, the present invention employs the concept of an“exposure event” or a “dose event” as the correlation in time and inspatial location with the measurement of a source of hazardous material,such as a radiation source, a hazardous chemical substance, or abiological agent. In one embodiment, the present invention provides amethod and apparatus for determining motion activity events by analysisof motion, time and dose information collected during the exposureevent.

In one embodiment of the present invention, motion activity (motiondata) is obtained by analysis of the displacement output from anaccelerometer or, optionally, the rotational displacement output from agyroscope or, optionally, the power signature from an energy harvesteror, optionally, other sensors that produce an output signal whoseamplitude varies as a function of motion.

In one embodiment of the present invention, position information(location data) is obtained from wireless communication systems such aswireless base stations or hubs or, optionally, from other wirelessdevices that communicate spatial positioning information such asBluetooth location beacons or, optionally, from a global positioningsystem (GPS).

In one embodiment of the present invention, exposure information isobtained from one or more sensors, which may include non-ionizingradiation such as UV or infrared light, ionizing radiation such as betaradiation, x-rays or gamma-rays, chemical substances such as hazardousliquids or gasses, or biological agents such as infectious bacteria,viruses, mold or other types of fungus or microbes.

In one embodiment of the present invention, time information is obtainedfrom an on-board clock.

In one embodiment of the present invention, additional information thatis useful in characterizing exposure events may be obtained from otheron-board sensors such as temperature, pressure or humidity sensors.

As shown in FIG. 1, an exemplary sensor array 100 comprising MEMS andnanotechnology manufacturing techniques are employed to create aconfiguration of encapsulating radiation attenuating material aroundrespective nanoscale radiation sensors. As illustrated, a plurality ofionizing radiation sensors 102 are provided and configurable, forexample, to be integrated on electronic chip circuitry, as discussedbelow. Ionizing radiation sensors 102 may include solid state sensortechnology including a detecting surface 114 of the sensor.

Ionizing radiation sensors 102 may be arranged into modular sensorarrays 204 (FIG. 2) comprising one or more radiation sensors 102 andmounted on a printed circuit board (PCB), for example, as describedbelow.

FIG. 1 illustrates a first sensor 104 encapsulated, for example, in afilter material such as a specific radiation attenuating material 108 ora “filtration bubble” 110 having, for example, a prescribed thickness.Up to “n” sensors 106 may be manufactured and encapsulated in up to “n”different respective filtration bubbles 112, where each filtrationbubble can consist of a similar or different materials or similar ordifferent material thicknesses. In this example, filtration bubble 108corresponds to sensor 106 such that sensor 106 is surrounded orencapsulated by filtration bubble 108. In some preferred embodiments,the filtration bubble may comprise a spherical geometry, or arectilinear or other geometry to cover the sensor to provide an optimalangular response wherein the response of the sensor is independent ofthe angle of incidence of the radiation or other measured quantity, suchthat the output of sensor 106 is the same at any angle (i.e., the filteris designed to produce a “flat” response at any angle). Materials of thefiltration bubble may include thin metallic layers including, forexample, copper, tin, aluminum, tungsten, etc. The filtration bubblewill characteristically be comprised of radiation attenuatingmaterial(s) capable of filtering out, for example, alpha particles andbeta radiation. Filter material such as specific radiation attenuatingmaterial 108 or a “filtration bubble” provides an optimal angularresponse wherein the response of the sensor is independent of the angleof incidence of the radiation (or other measured quantity), i.e., theoutput of sensor 106 is the same (or “flat”) at all angles.

Additional aspects of the disclosed invention provide the use of MEMSand nanotechnology sensors to simultaneously detect motion, globalposition, radiation exposure, and a process, such as the use of asoftware algorithm, to correlate radiation exposure levels over timewith motion of the detector and with the global position of thedetector. Accordingly, features of disclosed embodiments enable, atleast, the following advantages: (1) providing the correlation ofradiation exposure levels with time, motion and global position of thedetector to provide unique and valuable information on how the exposureoccurred; (2) allowing the global position to detect either via anon-board position locating sensor, such as a GPS sensor, or by aconnected external electrical device, such as a mobile smart device(e.g., smartphone), with a built-in GPS sensor or by estimation from amesh of networked devices; (3) providing enablement such that the time,motion and global position can be optionally recorded when the detectedexposure exceeds a threshold level.

Hardware components of the disclosed invention are further illustratedin FIG. 2 wherein modular sensors are integrated on a single chip orelectronic board 202 (e.g., PCB) thus forming an integrated sensormodule 200. Integrated sensor module 200 collects radiation data and isconfigured to ultimately transmit the data to a remote location such asa wireless base station or other wireless communications device. Theintegrated sensor module 200 is designed to be an independent sensorsystem that can be incorporated into many different form factor devices.The small size and self-contained nature of the integrated sensor module200 to be integrated into a wide range of devices such as a badge,nametag, key chain, bracelet, wrist watch, portable electronic device,MP3 Player, pager, cell phone, smartphone, laptop, tablet, glasses,article of clothing, wallet, purse or jewelry.

The primary sensor array 220 can either be a single sensor, a lineararray of sensors, or a matrix of sensors to form the primary or modularsensor array 204, for example employed from the sensor array 100 ofFIG. 1. Thus the modular sensor array 204 may utilize only a firstsensor #1 (212). Alternatively, modular sensor array 204 may comprise nnumber of rows such as from first sensor #1 (212) to sensor # n (214).Alternatively and/or in addition, modular sensor array 204 may include mnumber of columns such as from first sensor #1 (212) to sensor # m(216). Thus, having n number of rows and m number of columns, modularsensor array 204 would extend from first sensor #1 (212) to sensor # m,n (218).

While ionizing radiation sensors 102 encapsulated within “filtrationbubbles” 108 are shown for illustrative purposes, those skilled in theart will readily appreciate that the primary sensor array 220 mayconsist of other suitable types of sensors (e.g., for non-ionizingradiation, hazardous chemicals, or other biochemical substances).Alternative embodiments of the disclosed invention may also includechemical or other sensors in addition and/or as an alternative toionizing radiation sensor 102. The present invention describes anintegrated sensor module 200 that provides unique information about thelocation and the motion of the sensor when a measurement is obtained.The modular nature of the described platform and device enables the useof other individual sensors or as variable combination of sensors chosento meet the needs of potential end users. The modularity is achieved bydeveloping the measurement devices as interchangeable modules that canbe coupled to a central processing unit (CPU) that handles thecollection of time, motion, position and temperature and thecommunication.

The primary sensor array 220 may be integrated with a motion and globalposition sensor package The motion and global position sensor package206 will consist of a single 3-axis MEMS based accelerometer 222 thatwill determine if a primary data exposure occurs while the device isstationary or in motion as measured on a continual basis. A primary dataexposure is a radiological event recorded by the primary sensor array220. The motion and global position sensor package 206 will consist of aglobal positioning system (GPS) radio 223 that will determine itsposition by either the on-board GPS radio 223 and/or by a connectedwireless-enabled mobile device (e.g., smartphone or tablet with GPSsensing capability, etc.) or by estimation through a mesh of networkeddevices. To minimize power consumption of the primary power source thedevice will preferentially determine location through GPS sensors withthe lowest power means available to it. First by the connectedwireless-enabled mobile device with GPS capability, second by onboardGPS sensor and third by estimation through a mesh of networked devices.

Although one type of motion and global position sensor package is showin the integrated modular sensor of FIG. 2, other types of motion andglobal position sensor packages may be used in the present invention.For example, the motion and global position sensor package may includeadditional types of motion sensors in addition to or instead of anaccelerometer.

A wireless system on a chip (SOC) module 208 is configured to integratedsensor module 200. The wireless SOC module 208 is an integrated packageconsisting of a central processing unit and the wireless transceiver.Combining the wireless transceiver into the CPU chip in a SOCconfiguration allows a reduction in footprint and energy consumption.The wireless SOC module 208 permits wireless transmission fromintegrated sensor module 200, for example, to a wireless receiver ofanother electronic device for electronic communication purpose(s). Suchcommunications ability facilitates efforts, for example, in determiningwhether integrated sensor module 200 is within range of theaforementioned electronic device as further discussed below.

The power harvester 210 will consist of one or more energy harvestingdevices. A power harvester 210 is incorporated into the integratedsensor module 200 and connected to the battery. Power harvester 210collects energy via motion and/or movement of the integrated sensormodule 200 and the ambient light to recharge the battery that suppliespower to electronic board 202. Thus, the present invention will activelyconsume power as it operates and actively communicates to externalwireless enabled devices. Power harvester 210 leverages existing workwithin the MEMS devices to convert periodic (resonant) vibrationalmechanical motion into electrical energy to extend the battery thatpowers the runtime of the radiation measurement sensor capability of theintegrated sensor module 200.

Through extensive historical data on the dose levels of personalmonitoring radiation detectors it has been determined that 95% of usersreceive normal occupational level doses. By optionally collecting motionand position only when the detected exposure exceeds a preset threshold.The power consumption of the device can be greatly reduced. Thecombination of primary exposure data, time, motion and location createsa unique data set which may provide information about the location ofradiation fields and the motion of the users through those fields.

Embodiments of the disclosed invention enable the use of ultra-low-powerwireless transmission to transmit measured sensor readings fromintegrated sensor module 200 to a wireless-enabled mobile device (e.g.,a smartphone or tablet device, etc.), and the transmission of thisinformation over a wired or wireless data network to an Internet-basedserver.

The uniquely configured electronic modular configuration of thedisclosed invention provides several advantages. The filter material ismachine pressed into a spherical shape, and the resulting “filtrationbubble” 110 is mechanically pressed into the circuit board containingthe ionizing radiation sensor elements 102. Disclosed embodiments of theinvention will enact a unique software algorithm (as detailed below) toenable the discrimination between different types of ionizing radiationand different radiation energies. This enables a unique customization ofthe energy discrimination filtration scheme to improve the accuracy andenergy resolution of ionizing radiation measurements using a passiveradiation detector.

Radiation attenuating materials 108 are used to modify the response ofnon-tissue equivalent sensors to allow varying responses to a wide rangeof radiation qualities. The modified response can then be used by analgorithm to derive the tissue equivalent dose. Currently macro-filtersutilized in convention sensor devices have several shortcomings thatlimit the effectiveness of algorithms by introducing uncontrolledvariances. The use of MEMS and nanotechnology manufacturing process toencapsulate the radiation sensors with “filtration bubble” 110 providesseveral advantages over the traditional macro-filters that will helpeliminate the uncontrolled variances. The use of precise MEMS andnanotechnology manufacturing processes allows for the elimination ofmacro scale variances in the separation of the filter, thickness of thefilter and location of the filter. The filtration bubble 110 willeliminate macro scale issues with angular dependence of the filtration.The filtration bubble 110 will also provide a protective layer over thesensitive and possibly fragile sensor 102. The use of multipleattenuating materials 108 around multiple sensors 102 with the use of asoftware algorithm will allow increased levels of fine discriminationbetween types of ionizing radiation and radiation energy.

Additional advantages of the described embodiments of the presentinvention utilize MEMS and nanotechnology sensors to simultaneouslydetect radiation and other exposure, temperature, time, motion andglobal position, in combination with an employed software algorithm tocorrelate exposure levels. Detection occurs with the time, motion andglobal position of the integrated sensor module 200 wherein theintegrated sensor module 200 provides unique and valuable information onhow the exposure occurred. The use of modular exposure sensors enablesthe detection and analysis of exposure to a wide range of phenomenaincluding, for example, radiological, chemical, biological andelectromagnetic sources of exposure. The use of time, motion andposition further enables the determination of whether the integratedsensor module 200 was moving during an exposure event (e.g., staticversus dynamic exposures), and when and where the exposure occurred. Thepresent invention replaces the computationally intensive andtime-consuming post-processing and analysis that is currently used byconvention sensor devices to determine static versus dynamic exposures.The present invention also provides new time, position and otherinformation that may be used to accurately characterize the source andnature of the exposure. This capability may be particularlyimportant/useful in occupational dosimetry. The inclusion of atemperature sensor is disclosed embodiments enables correction ofmeasurements for temperature-based variance.

Furthermore, the present invention expands the capabilities andapplication of traditional, standalone dosimeters by allowing collecteddata to be transmitted to a central location for processing andredistribution as shown in FIG. 3. FIG. 3 illustrates a remote sensornetwork 300 according to an exemplary embodiment of the invention.Integrated sensor module 200 is integrated into a dosimetry badge 310.Dosimetry badge 310 is illustrated as a package, for example, includingthe disclosed electronics packaging including integrated sensor module200, batteries and a cover of the present invention. Integrated sensormodule 200 collects radiation data and ultimately transmits the data toa remote location such as a wireless base station or other wirelesscommunications device such as mobile communications device 308. A remotesensor chip of integrated sensor module 200 may be utilized to transmitthe data. In this case, the data may be transmitted via an unspecifiedwireless transmission communication protocol 312 such as Bluetooth®,ZigBee, ANT, or other standard Wi-Fi protocol, etc.

Examples of mobile communication device 308 may include, for example, asmartphone, tablet or a mobile hot-spot, or it might be a non-mobilenetwork device such as a dedicated base station. Mobile communicationdevice 308 may be configured to include a wireless transmitter andreceiver 316, data network interface 318, and GPS 320. Wireless SOCmodule 208 of integrated sensor module 200 is configured to communicatewith wireless transmitter and receiver 316. The wireless transmitter andreceiver may be a low powered wireless network interface for the mobilecommunication device 308. The network interface allows the mobilecommunication device 308 to communicate with SOC module 208 to downloadcollected data. The aforementioned communication facilitates thedetermination of whether mobile communication device 308 is in range ofintegrated sensor module 200.

Mobile communication device 308 may also be configured to include a datanetwork interface 318. The data network interface 318 allows mobilecommunication device 308 to communicate to another wide area wirelessnetwork 306 such as via data network transmission communication protocol314. Examples of data network transmission communication protocol 314may include Wifi, GSM/EDGE, CDMA, UTMS/HSPA+, LTE or other high speedwireless data communication network. Thus, in an exemplary embodiment,Bluetooth® may be employed to communicate between the dosimetry badge310 and mobile communication device 308 (such as via wirelesstransmission communication protocol 312), and the use of LTE tocommunicate between mobile communication device 308 and wireless network306 (such as via data network transmission communication protocol 314)of a remote facility such as a hospital or laboratory. In this example,the local network may be represented by wireless network 306 and thepublic network may be indicated by as public data network 302. Bycommunicating, for example, over the public data network 302, theaforementioned remote facility, such as a hospital or laboratory, mayreach, access and/or process information deposited on distributed dataserver 804.

GPS 320 enables mobile communication device 308 to determine theposition of the radiological event. The GPS 320 radio in the mobilecommunication device 308 provides an alternative means of thedetermining the position of the integrated sensor module 200. If theintegrated sensor module 200 has been paired with a mobile communicationdevice 308, it will preferentially use GPS sensor 320 to determinelocation to minimize its own power consumption.

Wireless network 306 is configured to communicate with the public datanetwork (e.g., the Internet) 302. A remote data server 304 is configuredto communicate with a public data network (e.g., the Internet) 302.

With an electronic data transmission link formed between mobilecommunication device 308 and remote data server 304, integrated sensormodule 200 is capable of transmitting measured data such as to anultra-low-power wireless-enabled mobile communication device 308 (e.g.,a smartphone, tablet or other mobile or non-mobile network device) toleverage the mobile device's existing data or cellular network tocommunicate collected information to a central web server and,optionally, to use the mobile communication device GPS, or to processthe collected data using the mobile communication device CPU. Currently,standalone sensor devices have limited power capacity that must beconserved as much as possible in order to extend battery life.Ultra-low-power wireless communication minimizes the power consumptionof device for regular updates. Furthermore, typical data or cellularcommunication antennas can consume significant power, so utilizing anexternal mobile communication device also limits the complexity ofradiation sensor.

Thus, the use of ultra-low-power wireless transmission capability of thepresent invention allows transmission of measured sensor readings fromintegrated sensor module 200 to a wireless-enabled mobile device 308(e.g., a smartphone or tablet device, etc.), and the transmission ofthis information over a wireless data network 306 to an Internet-basedserver 302. This enables the analysis and reporting of measured dosesfor individual detectors employing integrated sensor module 200 withouthaving to physically send the detector itself to a central location forreading and analysis. The reduces costs and valuable time for receivingdata and performing critical analysis. Embodiments of the presentinvention also allow for multiple systems to receive a plurality ofmeasured doses from a plurality of detectors having integrated sensormodule 200. The collection of sensor data from multiple systems enablesthe analysis and visualization and geographic-based mapping of exposuresources and related population-based trends over time. The connection tothe Internet also enables the remote update and troubleshooting of thedevice.

Disclosed embodiments of the present invention may include mounting theintegrated sensor module 200, for example, on multiple, low-cost,semi-autonomous unmanned airborne vehicles (UAV's) such as low-power RFhelicopters. A flocking-algorithm may be employed to cause the “flock”of devices to track the position and distribution of airborne radiation,chemicals or other phenomena while remaining in the flock and where thedistribution of the flock would correlate with the distribution of theairborne material being tracked.

Thus, in select embodiments, the disclosed invention enables theintegration of the integrated sensor module 200 into a mobile platformthat may consist of multiple semi-autonomous UAV's to track the positionand distribution of airborne materials (radiation, chemicals, biologicalagents, electromagnetic fields, etc.). The UAV-integrated sensors mayutilize flocking algorithms to coordinate between multiple UAV's andtrack the position and distribution of airborne particles. Turning toFIG. 4 an exemplary autonomous mobile sensor (AMS) network 400 isillustrated. As shown in FIG. 4, the airborne (or waterborne) particles402 will tend to cluster and then distribute depending, for example,upon prevailing weather patterns. Autonomous mobile sensors (AMS) 404,406 are shown tracking respective distributed target particles 408, 410.The flocking algorithm will update the position of all UAVs 404, 406 byusing a Sensor Force, Fs, proportional to the measurement from themodular sensor array 204 on the UAV, and a Flocking Force, Ff,proportional to the distance to nearby UAV's, to continually optimizethe positions of the UAV sensors 404, 406 and to best track the positionof the target particles 408, 410. As a result, the distribution of theflock will also correlate with the distribution of the airborne materialbeing tracked.

In another embodiment the disclosed invention may include mountingintegrated sensor module 200 on multiple, low-cost, semi-autonomous andunmanned water-based vehicles and tracking, for example, waterborneparticles. Again, the use of the previously described flocking-algorithmmay be employed to coordinate between multiple unmanned water-basedvehicles and to track the position and distribution of any water-basedradiation, chemicals or other phenomena.

Advantages of the disclosed invention provide the first use of MEMS andnanotechnology to create a passive integrating electronic ionizingradiation detector with active readout capability and withmotion-sensing and position-sensing capabilities and wirelesstransmission of the sensor readings. Current active dosimeters requirecontinuous power in order to measure dose. Additionally, current passivedosimeters do not provide immediate access to recorded dosemeasurements. Furthermore, the active readout of a passive radiationsensor disclosed by the present invention provides immediate access todose information while preserving dose information in the event of powerloss. In addition, the present invention describes an electronicplatform for recording motion, temperature and position with modularenvironmental sensors for comprehensive personal and environmentalmonitoring.

An exemplary integrated sensor module logic flow 500 for integratedsensor module 200 is represented in FIG. 5. A command 502 for readingthe sensor is executed. Command 502 includes pre-reading ahigh-sensitivity sensor 504 to determine if there is a new thresholddose 506 on the sensor.

In determining whether there is a new threshold dose 506 on the sensor,the sensor is enabled to continuously accumulate dose values. When aread is performed on a specially-designated high-sensitivity sensor(referred to hereinafter as a “pre-read” of the dosimeter), then acumulative value is generated. The previous dose value is subtractedfrom the cumulative value generated from the pre-read to generate adelta (Δ) value. If the delta (Δ) value above a prescribed dosethreshold, then a trigger measurement is taken in step 508. If the delta(Δ) value is not above the prescribed dose threshold then a loopbackfunction is performed to take continuous measurements at a timedinterval to read the sensor 502. Described embodiments continuously loopback to pre-read high-sensitivity sensor 504 until a delta (Δ) dosevalue is detected to be higher than the prescribed dose threshold value.Once a delta (Δ) dose value is detected to be higher than the prescribeddose threshold value, a trigger measurement 508 is enabled tosimultaneously read a solid-state sensor array 510 (also see FIG. 6) andread-out of the event data or position of exposure in time 512 (also seeFIG. 7).

One disclosed embodiment of the sensor readout logic flow diagram isillustrated in FIG. 6. The solid-state sensor array read-out 600 is thecomponent of the disclosed invention that reads the entire sensor array.A reading from the high-sensitivity sensor indicates that the minimumincremental dose threshold has been reached. The high-sensitivity sensoris solely intended to indicate when the threshold dose has beenexceeded. Once the threshold dose has been exceeded, then all of thesensors will be read from a 1-D array, a 2-D array or a 3-D matrix. A1-D array may just be a row of sensors. A 2-D array may be a table ofsensors or a matrix of sensors. A 3-D array would be if you stack upmultiple 2-D arrays. There are multiple ways of reading the measurementsfrom the sensors. We could either read each sensor individually 602, orwe might read-out along an entire row or column of sensors 604, or wemight sum up the output from all of the sensors 606, or we might readouta custom configuration (e.g., four of the sensors in each quadrant ifthere was an array of multiple sensors (e.g., sixteen sensors). Hence,disclosed embodiments of the described invention provide multiple waysof reading a solid-state sensor array.

One disclosed embodiment of the sensor readout logic flow diagram isillustrated in FIG. 6. The solid-state sensor array read-out 600 is thecomponent of the disclosed invention that reads the entire sensor array.In one example, the high sensitivity sensor may be affixed to a badge.In an event where the badge is exposed to ionizing radiation thedisclosed invention can read-out all of the sensors required tocalculate the exposed dose. Disclosed embodiments provide the ability toread individual, a whole array of sensors, and a custom configuration ofsensors. Accordingly, for various configurations of sensors, theinvention may generate readings, for example, for individual sensors 602such as a one-dimensional array including, for example, a row ofsensors. In addition to, or alternatively, dimensional arrays of sensorsmay be read by disclosed embodiments to include, for example, a table ofsensors or a matrix of sensors. Such embodiments of sensorconfigurations may include a two-dimensional array of sensors including,for example, one or more rows or one or more columns of sensors.Disclosed embodiments may also provide a three-dimensional array, forexample, including one or more two-dimensional arrays stacked upon oneanother. Thus, disclosed embodiments may either read sensorsindividually 602, perform a two-dimensional read-out, for example, alongan entire row or column of sensors 604, or perform a sum of all of theoutput from all of the sensors 606, or perform a readout for a customconfiguration of sensors (e.g., four of the sensors in each quadrant ifthere was an array of multiple sensors (e.g., sixteen sensors)). Hence,disclosed embodiments of the described invention provide multiple waysof reading a solid-state sensor array.

Disclosed embodiments provide electronic sensing circuitry to generatean analog measurement. The analog measurement is preferably converted toa digital measurement utilizing standard analog to digital conversioncircuitry 610. From the digital data, the dose 612 is calculated byimplementing an algorithm of the disclosed invention for calculating thedose on a system on a chip (SOC) (e.g., via an arm processor). Thecalculated dose value is then recorded on a data record 614 which mayessentially generate a log of all of the readings on an ongoing basis.

In parallel with the solid-state sensor array read-out 600 of FIG. 6,the disclosed invention executes a read-out of the event data orposition of exposure in time 512. The position of exposure read-outlogic flow 700 is illustrated in FIG. 7 and may be executed via parallelcircuitry. An on-board MEMS accelerometer device 702 is read todetermine if the sensor is in motion. Next, the location (which can beconsidered the position in space with a specified level of granularityor spatial resolution) of the sensor is estimated at step 704. This maybe accomplished, for example, by reading the GPS sensor on theintegrated sensor module, or by using wireless communication to obtainthe location from external location beacons, or by using an on-boardalgorithm to estimate the location (e.g., using a “dead-reckoning”algorithm), or by communicating with a mobile device (e.g., cell phone)in which the GPS function of the mobile device is utilized to determinethe geospatial position, or by estimating the location by triangulationbetween external location beacons or other dosimeters.

In one embodiment of the present invention using GPS, the GPS receiverof the mobile device determines position by precisely timing the signalssent by GPS satellites. Each satellite continually transmits messagesthat include the time the message was transmitted and the satelliteposition at the time of message transmission. The GPS receiver uses themessages it receives to determine the transit time of each message andcomputes the distance to each satellite using the speed of light. Eachof these distances and satellites' locations define a sphere. Thereceiver is on the surface of each of these spheres when the distancesand the satellites' locations are correct. These distances andsatellites' locations are used to compute the location of the receiverusing navigation equations. In another embodiment, the position may beestimated by triangulating the position such as from a known wirelesshub with which the sensor is communicating. Wireless triangulation isthe process of determining a location of a point by measuring signalstrength between several nodes of the wireless network. A time stamp isgenerated at step 706 to record the time at which a measurement wastaken. This measure correlates to the motion (e.g., point at whichon-board MEMS accelerometer device is read 702) and position (e.g., theestimated position of the sensor at step 704) at the time the sensor wasread. The time stamp readings from step 706 may then be exported orrecorded to the data log. Thus, the exposure event is captured in thedata record 708.

Turning again to FIG. 5, the above description outlines the generationof a dose value 510 and a position of exposure in time 512 in the log orrecorded data records 614 and 708, respectively, to generate a completedata record 514. The complete data record 514 is saved or updated to therecord log and the Send Timer is checked 516. The Send Timer determineswhen data should be uploaded to the base station 802 or mobilecommunication device 308 based on a programmable Time To Send value. Forexample, if the dose exceeds a prescribed threshold value or if theprescribed time has elapsed, then the dose value is transmitted andrecorded 522. If the Time to Send value has not been reached, then thedevice will return to reading 520.

The wireless transmission is started 524 in order to initiate sending asignal from the sensor wireless SOC module 208 of the integrated sensormodule 200, for example, to wireless receiver 316 of mobilecommunication device 308. The sensor's wireless SOC module 208 looks fora handshake response from the wireless transmitter 316 of the mobilecommunications device 308 to determine if the device is in range forfurther communication. Wireless SOC module 208 of the integrated sensormodule 200 can be configured to communicate with another electroniccommunications device, such as base station 802, to determine if it iswithin range of the electronic communications device. If a receiver iswithin range and a response is received, then the operation continues528. If a determination is made that the sensor is not in range, then adetermination of “no” is made 526 and the operation returns to read thesensor 502 again. When a determination is made that the sensor is inrange, a determination of “yes” is made 528, and the data record istransmitted such that the log is updated to show that the data recordhas been transmitted 530 and to record that the system has been updated.A continuous, never-ending number of readings may occur or as needed inthe integrated sensor module logic flow 500.

FIG. 8 illustrates an exemplary embodiment of the disclosed invention incommunication with a wireless sensor base station configuration 800. Oneor more generalized data servers can be connected to a public datanetwork, such as the Internet, to provide an event repository whereinall of the event data is stored in one or more databases accessible overthe Internet, and wherein further data analysis can be performed. TheInternet is sometimes referred to The Cloud, and access to data over TheCloud for further analysis is sometimes referred to as Cloud Computing.

Dosimetry badge 310 is illustrated as a package containing, for example,the disclosed electronics packaging including integrated sensor module200, batteries and a cover of the present invention. Using the algorithm(FIGS. 6 and 7), the integrated sensor module 200 is configured totransmit data to a wireless communications device such as a wirelesssensor base station 802. Dosimetry badge 310 may communicate withwireless sensor base station 802 via an unspecified wirelesstransmission communication protocol including, for example, Bluetooth®,Bluetooth Low Energy (BLE), ZigBee, ANT, ANT+ or other standard wirelesscommunications protocols.

Wireless sensor base station 802 includes a wireless transmitter andreceiver 816. Wireless SOC module 208 of integrated sensor module 200communicates with wireless transmitter and receiver 816 to determinewhether base station 802 is in range of integrated sensor module 200 asdiscussed, for example, in step 532 of FIG. 5 above. Wireless sensorbase station 802 may also include a data network interface 818. Datanetwork interface 818 allows wireless sensor base station 802 tocommunicate to another wireless network such as via data networktransmission communication protocol 314. Thus, in an exemplaryembodiment, Bluetooth® Low Energy (BLE) may be employed to communicatebetween the dosimetry badge 310 and wireless sensor base station 802(such as via wireless transmission communication protocol 312), andWi-Fi may be employed to communicate between wireless sensor basestation 802 and wireless network 306 (such as via data networktransmission communication protocol 314) of a remote facility such as ahospital or laboratory. In this example, the local network may berepresented by wireless network 306 and the public network may beindicated by as public data network 302. By communicating, for example,over the public data network 302, the aforementioned remote facility,such as a hospital or laboratory, may reach, access and/or processinformation deposited on distributed data server 804.

In an optional configuration, wireless sensor base station 802 mayinclude integrated sensor module 200. This configuration enableswireless sensor base station 802 as an event sensing device as well,acting, for example, as an environmental sensor.

As previously discussed, disclosed embodiments of the invention mayemploy a unique, numerically optimized dose calculation algorithm,running in the embedded system software or, optionally, on thecloud-based server, to enable the discrimination between different typesof ionizing radiation and different radiation energies. This enables aunique customization of the energy discrimination filtration scheme toimprove the accuracy and energy resolution of ionizing radiationmeasurements using a passive radiation detector. Disclosed embodimentsprovide electronic sensing circuitry to generate an analog measurement.The analog measurement is preferably converted to a digital measureutilizing standard analog to digital conversion circuitry 610. From thedigital data, the dose 612 is calculated by implementing the algorithmof the disclosed invention for calculating the dose on a system on achip (SOC) (e.g., via an arm processor). Select embodiments may employ,for example, a machine readable medium having stored thereon sequencesof instructions, which when executed by one or more processors, causeone or more electronic devices to perform a set of operations to performthe aforementioned algorithm. The calculated dose value is then recordedon a data record 614 which may essentially generate a log of all of thereadings on a continuous basis.

Accordingly, an embodiment of the invention provides a numericallyoptimized dose calculation algorithm for accurate and reliable personaldosimetry. Disclosed embodiments provided a computational procedure togenerate numerically optimized dose calculation algorithms for personaldosimeters using multiple dosimeter elements (typically two-to-fourelements). Current embodiments provide a description of how methods ofthe present invention transforms dosimeter signals to operationalquantities for personal dose equivalents such as Hp(10), Hp(3), andHp(0.07). Some advantages of the computational procedure of thedisclosed invention include the ability to automatically generate anumerically optimized algorithm, the absence of branching or empiricaldecision points, and fast computation speed.

The accurate and reliable measurement of a personal dose equivalent is akey component of radiation dosimetry programs. The personal doseequivalent is typically measured over a wide range of energies and fromdifferent radiation sources, including, for example, x-ray and gammaphotons, beta particles and neutrons. In order to accurately estimatethe dose from different radiation sources, some personal dosimetersincorporate multiple detector elements, each with varying types ofradiation filtration materials, and use a dose calculation algorithm, tocalculate the personal dose equivalent from a numerical combination ofthe responses from each detector element.

One approach to calculate the dose is to use a simple linear combinationof detector element responses. Such approaches are straight-forward andeasy to implement, but may be highly sensitive to noise and often do notreliably provide an accurate estimate of the dose under realisticconditions. Another approach is to use empirically-determined branchingand decision points. According to exemplary embodiments, this approachis relatively easy to implement, and improves performance under someconditions, but the empirical decisions are unique to specificconditions, and often subject to systematic biases. Techniques forapplying both linear combination and branching methods to radiationdosimetry have been developed, for example, by N. Stanford (e.g., see N.Stanford, Whole Body Dose Algorithm for the Landauer InLight NextGeneration Dosimeter, Algorithm Revision: Next Gen IEC; Sep. 13, 2010and N. Stanford, Whole Body Dose Algorithm for the Landauer InLight NextGeneration Dosimeter, Algorithm Revision: Next Gen NVLAP; Sep. 27,2010).

The present invention provides MATRIX i.e., a computational procedure toautomatically generate a dose calculation algorithm that is numericallyoptimized for a particular dosimeter type (i.e., a particularcombination of dosimeter detector elements and filters). In order tominimize systematic bias the disclosed embodiment, i.e., MATRIXcalculates a weighted average from representative data, such that no oneirradiation field, detector or ratio of detector signals dominates theresultant dose. The following describes the computational procedure usedto generate a numerically-optimized dose calculation algorithm for apersonal dosimeter using a matrix of element responses obtained frommeasurements of that type of dosimeter.

Given a personal dosimeter consisting, for example, of multiple filtereddetector elements, the detected signal from each detector element iscalled the element response, and the array of element responses from agiven dosimeter is called the detector's element response pattern. For agiven type of dosimeter, the matrix resulting from multiple detectorelement responses at different but known irradiations is called theelement response matrix.

The element response matrix is created by exposing a dosimeter to knownirradiations at different angles and to mixtures of individual ormultiple sources, and then reading the element responses from eachdetector element. The element response pattern from an unknownirradiated dosimeter is then compared to the patterns in the elementresponse matrix, and a dose is calculated for each source in theresponse matrix. The final reported dose is the sum of all theindividual source doses weighted by a Source Probability Factor. TheSource Probability Factor is a measure of how closely the elementresponse pattern of the unknown dosimeter matches the individual elementresponse pattern of known sources.

The steps in the disclosed embodiment, i.e., MATRIX computationalprocedure 900 are summarized in Table 1 of FIG. 9, and eachcomputational procedure is described in the corresponding sectionsbelow.

In step 902, the dosimeter element responses and the correspondingdosimeter response matrix for that type of dosimeter are input, and thenthe converted values are calculated. For dosimeters employing opticallysimulated luminescence (OSL) such as LANDAUER's InLight® dosimeters, thedosimeter element responses correspond to the photomultiplier countsfrom the InLight® Reader. The converted values are calculated from thePMT counts as shown in Equation 1:

${ConV}_{n} = \frac{{PMT}\mspace{14mu} {Counts}_{n}}{{Sensit} \times {Reader\_ Cal}{\_ Factor}}$

The response matrix corresponding to the dosimeter type may be read fromcomputer storage. In one disclosed example, e.g., for LANDAUER InLight®dosimeters, the response matrix contains entries (variables) describingthe source, the individual element responses, the deep dose equivalent(DDE) conversion factor, and the standard deviations of the responses.

The response matrix selection may be based on empirically derived rules.In order to achieve optimal performance in a certain application, therange of sources in the response matrix is restricted. This techniquemay cause a systematic error if radiation conditions occur outside theselected range. An implementation of the disclosed embodiment usingselection cuts is described, for example, in Brahim Moreno, LDR-EuropeTechnical Report on a Hybrid MATRIX-Branching dose calculationalgorithm, 2013.

Next a dose calculation may be performed. Given a set of measuredconverted values, the first step is to calculate G1-4 for each field inthe response matrix. Note that the values of G for a given fieldindicate what the SDE would be if the given field matched the actualincident field to the dosimeter.

The expected value of the SDE for a given field could be taken as thesimple average of G over the detector elements. This however would beinsufficient due to the fact that for some incident radiation fields,several detectors may have signals with high levels of uncertainty. Thisturns out to be the case with 85Kr β-rays incident upon detectors withfiltration over 0.1 g/cc in density thickness. Because of this field isweakly penetrating, the signals received from the filtered elements aretoo low relative to the noise level to use them to calculate dose.

A way to calculate dose using only detectors with a good signal is toweight the signal of each detector by a factor inversely proportional tothe expected uncertainty and then perform a weighted average over thedetectors. The first set is to define the expected uncertainty. Assumethat each response matrix entry is determined from data for which thecounting statistics were negligible (high dose). This error is acombination of the uncertainties due to the irradiation, reading,handling, and material variability. This combined error is computed asthe standard deviation of the data used to generate the response matrix,it is symbolized by σ.

The expected value of the SDE for field j is given by G_(j) . The totaluncertainty for the ith detector element and jth radiation field is bysymbolized by σ_(ij).

$\begin{matrix}{\overset{\_}{G_{j}} = \frac{\sum_{i = 1}^{4}\frac{G_{ij}}{\sigma_{ij}^{2}}}{\sum_{i = 1}^{4}\frac{1}{\sigma_{ij}^{2}}}} & (2)\end{matrix}$

A goodness of fit statistic for a single radiation field, j, is given inEquation 3.

$\begin{matrix}{s_{j} = \sqrt{\sum\limits_{i = 1}^{4}\; \left( \frac{G_{ij} - {\overset{\_}{G}}_{j}}{\sigma_{ij}{\overset{\_}{G}}_{j}} \right)^{2}}} & (3)\end{matrix}$

The weighting factor for field j is given in Equation 4.

$\begin{matrix}{W_{j} = \frac{1}{\left( {^{s_{j}} - 1} \right)^{2}}} & (4)\end{matrix}$

Now that a weighting factor has been assigned to each field in theresponse matrix, the reported SDE value, Grep, is calculated. This isdone by taking the weighted sum of the expected values for eachradiation field G _(j), over the entire response matrix. This is givenin Equation 5, where the sum is performed over a response matrix of Nfields.

$\begin{matrix}{G_{rep} = \frac{\sum_{j = 1}^{N}{W_{j}{\overset{\_}{G}}_{j}}}{\sum_{j = 1}^{N}W_{j}}} & (5)\end{matrix}$

The quantification of similarity between the response pattern of ameasured set of converted values and the fields in the response matrixcan be derived using any optimization technique. Equations 3-4 are basedon the χ2 minimization. The source specific statistic and weightingfactor are an empirical measure of how well the pattern of a set ofmeasured converted values matches the patterns found in the responsematrix.

In step 904, a check for error conditions is performed. In this step,common error conditions are checked and, if detected, the appropriateerror conditions are set. The dose is not reported if a serious errorcondition is detected.

In step 906, dose values are calculated for each source in the responsematrix. In this step, a weighted value for Hp(0.07) and Hp(10) arecalculated for each element to form the response pattern for thisdosimeter. Then a goodness of fit statistic is calculated, and then asource weighting factor is determined.

In step 908, disclosed embodiments calculate the total reportable doses.In this step, the weighted values for Hp(0.07) and Hp(10) for eachelement are summed, then the source weighting factors for each elementare summed. The reportable Hp(0.07) and Hp(10) doses are calculated.

In step 910, an estimate of the most likely source of radiation isperformed. In this step, the probable contribution of each source in theresponse matrix is estimated. In the currently disclosed algorithm, theprobable contribution of photons and beta particles is estimated.

In step 912, the final (net) dose values are calculated. In this step,the net dose is calculated by subtracting a control dose from thepreviously calculated dose. Only net doses greater than 1.0 mrem arereported.

In step 914, the net dose values are outputted, e.g., from memory tostorage device. In this step, the net dose is assigned to a specificdosimeter using the unique identification value stored in the dosimeterinformation database. The calculated Net Dose in computer memory isstored in the database (or exported to an external data file if needed.The results can be formatted to allow the generation of dose-of-recordcustomer dose reports as required by local, national or internationalregulations.

A flowchart 1000 of the disclosed computational procedure for employingan algorithm to generate numerically optimized radiation dosecalculations for personal dosimeters is illustrated in FIG. 10.Information/data from the dosimeter readout 1004, background radiationdose 1006 and response matrix 1008 may be read and inputted from acomputer storage 1002 such as a computer disk and stored to a machinereadable medium such as memory 1010. The machine readable medium ormemory 1010 may have stored thereon sequences of instructions, whichwhen executed, for example, by one or more processors, may cause one ormore electronic devices to perform a set of operations to perform thedisclosed computer algorithm. The disclosed computer algorithm processesthe raw data (e.g., dosimeter readout 1004, background radiation dose1006, and response matrix 1008) and transforms it to useful informationwhich may be further written to a computer storage 1016 such as acomputer disk where the information may be configured to be displayed asneeded.

After the raw data is received to memory 1010, disclosed embodimentscheck for error conditions 1012. Common error conditions are checkedand, if detected, the error may be flagged 1014 and all errors may betracked/tabulated on computer storage 1016. If there is no error 1018,the raw data is processed by the disclosed computer algorithm 1020.Computer algorithm 1020 begins by applying a mathematical algorithmusing prescribed numerical procedures to optimize the response matrix.This may include calculating the expected source dose with adata-fitting procedure. The inputs are the converted values and sourceresponses. The response matrix weighting factor may be calculated usinga goodness-of-fit statistic. The weighting factors tell you how mucheach source contributes to the final dose. An optimization technique maybe selected based upon prescribed performance criteria. The Dosecontribution may be calculated from the product of the weighting factor,expected source does, and dose conversion factor for personal doseequivalent (e.g., Hp(10 mm), Hp (0.07 mm), and Hp (3 mm)).

Once the optimal fit is found/determined, the reportable doses arecalculated 1022 by summing the dose contributions for each source outputdose. Radiation quality is assessed 1024 by performing a sum over theweighting factors multiplied by the source energy and particleidentification. The radiation quality may be written to computer storage1028 such as to computer storage 1016. The net dose is calculated bysubtracting the reportable doses and background dose. The net doses maybe written to computer storage 1030 such as to computer storage 1016.

There is a surge in interest in energy harvesting from human motion dueto the rising demand for wearable electronics, such as for patientmonitoring in healthcare applications and wearable consumerproducts^(13,14). However, human vibration and motion energy isgenerally concentrated below 10 Hz, which may cause difficulty becauselower frequency sources are more difficult to design for due to therequirement of either a highly compliant spring or large mass.

The present invention uses energy harvesting through micro mechanicalsystems (MEMS) and photovoltaic systems to recharge the internal batteryand extend the powered lifetime of the integrated sensor module 200.Embodiments of the disclosed invention also extend previous work usingthe MEMS devices of the integrated sensor module 200 to convert resonantand vibrational mechanical motion into electrical energy andphotovoltaic cells to convert ambient lighting into electrical energy.The present invention uses MEMS to convert the random mechanical energyof human motion into electrical energy, and photovoltaics to convertambient light into electrical energy, both of which can be stored in abattery on the device and later used to power the above-describedsensors of the integrated sensor module 200. MEMS based energyharvesting can be accomplished with piezoelectric, electrostatic ormagneto-static devices. Disclosed embodiments may detect vibration andmotion energy at general concentrations below 10 Hz. Furthermore,disclosed embodiments provide a power harvester, wherein the powerharvester converts mechanical vibration energy into electrical energy,and wherein the resonant excitation of the power harvester has afrequency range of approximately 6-8 Hz.

Select embodiments may employ the ability to adjust the energy harvesterto maximize the energy collected for a particular application. Forexample, the aforementioned may include, in a mechanical energyharvesting design, using a magnet and coil, wherein there exists theability to adjust the size of the coil, size and strength of themagnets, etc. Piezoelectric energy harvesters convert mechanical strainof vibration in electrical energy. Electrostatic energy harvesterscollect energy from the changing capacitance of vibrating, separated,charged parallel plate capacitors. Magneto-static energy harvesterscollect energy through the motion of a magnet near an electric coil,such that the changing magnetic field of the moving magnet inducescurrent flow in the electric coil. Photovoltaic energy harvesters arebased on solar cells that convert solar or ambient indoor light intoelectric current.

It is well appreciated that other non-limiting embodiments may beemployed, for example, conversion of heat (e.g., from a human or animalbody or combustive device, or other heat-generating thermocouples) intoelectrical energy suitable for use in a wireless sensor. Additionalembodiments may include conversion of radiofrequency energy intoelectrical energy suitable for use in a wireless sensor. Otherembodiments may employ a radiofrequency receiver coil to optimize theintegration of RF receiver coils and sensors, for example, into fabricor clothing materials in order to maximize energy collection and sensingcapabilities.

Disclosed embodiments address energy harvesting designs that may beemployed as a power source for the disclosed sensor. Recently,magnetically sprung, or levitating, electromagnetic energy harvestershave been studied by researchers¹⁵⁻²³. One key advantage of magneticlevitation is that the mechanical spring is replaced with a magneticspring, thus leading to an extended lifetime because the physical springis the most likely component to fail. Additionally, the removal of aphysical spring allows the spring constant to be designed very low,leading to a low resonant frequency. These characteristics make thelevitating electromagnetic type energy harvester ideal for human motionenergy harvesting.

In another embodiment, U.S. Pat. No. 8,692,206 B2 entitled “Systems,Devices, and Methods Including Implants for Managing Cumulative X-rayRadiation Dosage” issued to Hyde et al. on Apr. 8, 2014 and hereinincorporated by reference describes an implantable radiation sensingdevice including one or more power sources. The implantable radiationsensing device includes a power source including one or more generatorsconfigured to harvest mechanical energy from, for example, acousticwaves, mechanical vibration, blood flow, or the like. For example, in anembodiment, the power source includes at least one of abiological-subject (e.g., human)-powered generator, a thermoelectricgenerator, a piezoelectric generator, an electromechanical generator(e.g., a microelectromechanical system (MEMS) generator, or the like), abiomechanical-energy harvesting generator, or the like. In anembodiment, the power source is electromagnetically, magnetically,acoustically, optically, inductively, electrically, or capacitivelycoupled, for example, to at least one of the x-ray radiation sensordevice, the exposure determination device, a computing device, atransmitter, a receiver, a transceiver, etc.

Non-limiting examples of power sources examples include one or morebutton cells, chemical battery cells, a fuel cell, secondary cells,lithium ion cells, micro-electric patches, nickel metal hydride cells,silver-zinc cells, capacitors, super-capacitors, thin film secondarycells, ultra-capacitors, zinc-air cells, or the like. Furthernon-limiting examples of power sources include one or more generators(e.g., electrical generators, thermo energy-to-electrical energygenerators, mechanical-energy-to-electrical energy generators,micro-generators, nano-generators, or the like) such as, for example,thermoelectric generators, piezoelectric generators, electromechanicalgenerators, biomechanical-energy harvesting generators, or the like. Inan embodiment, the power source includes at least one rechargeable powersource. In an embodiment, the power source may include one or moremicro-batteries, thin film batteries, fuel cells (e.g., biofuel cells,chemical fuel cells etc.), or the like.

In an embodiment, the implantable radiation sensing device carries thepower source. The implantable radiation sensing device may include atleast one of a battery, a capacitor, or a mechanical energy store (e.g.,a spring, a flywheel, or the like). In an embodiment, the implantableradiation sensing device includes a power source including at least oneof a battery, a capacitor, or a rechargeable power or a mechanicalenergy store. In an embodiment, the power source is configured to managea duty cycle associated with, for example, detecting and quantifying atranscutaneously received x-ray radiation stimulus, in vivo.

In one embodiment of the present invention, thebiological-subject-powered generator is configured to harvest thermalenergy generated by the biological subject. In one embodiment, thebiological-subject-powered generator is configured to harvest energygenerated by the biological subject using at least one of athermoelectric generator, a piezoelectric generator, anelectromechanical generator (e.g., a microelectromechanical system(MEMS) generator, or the like), a biomechanical-energy harvestinggenerator, or the like. For example, in an embodiment, thebiological-subject-powered generator 1136 includes one or morethermoelectric generators configured to convert heat dissipated by thebiological subject into electricity. In an embodiment, thebiological-subject-powered generator is configured to harvest energygenerated by any physical motion or movement (e.g., walking, etc.) by abiological subject. For example, in an embodiment, thebiological-subject-powered generator is configured to harvest energygenerated by the movement of a joint within the biological subject. Inan embodiment, the biological-subject-powered generator is configured toharvest energy generated by the movement of a fluid (e.g., biologicalfluid) within the biological subject.

In an embodiment, the implantable radiation sensing device includes atranscutaneous energy transfer system. For example, in an embodiment,the implantable radiation sensing device includes one or more powerreceivers configured to receive power from at least one of an in vivo oran ex vivo power source. In an embodiment, the transcutaneous energytransfer system is electromagnetically, magnetically, acoustically,optically, inductively, electrically, or capacitively coupled to atleast one of the x-ray radiation sensor device the exposuredetermination device, the transmitter, the receiver, the transceiver, orthe like. In an embodiment, the transcutaneous energy transfer system isconfigured to transfer power from at least one of an in vivo or an exvivo power source to the implantable radiation sensing device.

In an embodiment, the transcutaneous energy transfer system isconfigured to transfer power to the implantable radiation sensing deviceand to recharge a power source within the implantable radiation sensingdevice. In an embodiment, the transcutaneous energy transfer system iselectromagnetically, magnetically, acoustically, optically, inductively,electrically, or capacitively coupleable to an in vivo power supply. Inan embodiment, the transcutaneous energy transfer system includes atleast one electromagnetically coupleable power supply, magneticallycoupleable power supply, acoustically coupleable power supply, opticallycoupleable power supply, inductively coupleable power supply,electrically coupleable power supply, or capacitively coupleable powersupply. In an embodiment, the energy transcutaneous transfer system isconfigured to wirelessly receive power from a remote power supply.

Since on-chip power is often not feasible, the source of power may haveto come from, for example, a magnetic field coupling. U.S. Pat.Application Pub. No. US 2010/0219494 A1 entitled “Sub-MM WirelessIonizing Radiation Detector” by Barnaby published Mar. 2, 2010 andherein incorporated by reference discloses a standard approachimplemented in many RFID products²⁴. In their 2008 paper, Beyer et al.successfully demonstrated the use of RF energy harvesting to power aMOSFET dosimeter and a bidirectional communication interface²⁴.

Currently, the majority of autonomous and mobile electronic systems arepowered by electrochemical batteries. Although the battery quality hassubstantially improved over the last two decades, their energy densityhas not greatly increased. At present, factors such as cost, weight.Limited service time and waste disposal problems (intrinsic tobatteries) are impeding the advance in many areas of electronics. Theproblem is particularly acute in the portable electronics market, whererapidly growing performance and sophistication of mobile electronicdevices has led to ever-increasing generating several watts powerdemands that traditional electrochemical batteries are unable to meet.

U.S. Pat. Application Pub. No. US 2012/0181901 A1 entitled “Method andApparatus for Mechanical Energy Harvesting Using Planar MicrofluidicDevice” by Krupenkin et al. published Jul. 19, 2012 and hereinincorporated by reference discloses an energy harvester whichillustrates a train of energy-producing conductive droplets locatedalong a microscopically thin channel, where droplets are suspendedwithin a liquid dielectric medium and are hydraulically actuated byapplying a pressure differential between the ends of channel.Pluralities of separate electrodes 5-1 and 5-2 are disposed along eitherside of channel, which engage with droplets as they move back and forthwithin channel during changes in pressure. As conductive droplets movealong channel, they create arrays of capacitors with electrodes 5-1 and5-2, the capacitors changing in stored charge as the droplets move backand worth, generating an electrical current flow. This type of hydraulicactivation method provides an important advantage as it allows forefficient direct coupling with a wide range of high power environmentalmechanical energy sources, including human locomotion.

While the microfluidic-based energy harvester of Krupenkin et al.exhibits a significant improvement over the state of the art, thisactuation method is not well-suited for applications where the energy isbeing harvested from mechanical vibrations, since the displacementamplitude of a vibration is often too small to initiate motion ofdroplets along a channel. Yet, such vibrations constitute a readilyavailable source of energy in many important environments, includingtransportation (e.g., automotive, aerospace, rail), industrialmachinery, and the like. Thus, any method that can provide effectiveactuation of microscopically small liquid droplets by environmentalmechanical vibrations would be highly beneficial, as it would allow forthe extension of energy harvesting to a broader range of environments.power demands that traditional electrochemical batteries are unable tomeet.

One of the technologies that holds great promise to substantiallyalleviate the current reliance on the electrochemical batteries is highpower energy harvesting. The concept of energy harvesting works towardsdeveloping self-powered devices that do not require replaceable powersupplies. In cases where high mobility and high power output isrequired, harvesters that convert mechanical energy into electricalenergy are particularly promising, inasmuch as they can tap into avariety of “high power density” energy sources that exhibit mechanicalvibrations.

High power harvesting of mechanical energy is a long-recognized concept,yet it has not been able to be commercialized, due at least in part tothe lack of a viable energy harvesting technology. Existing methods ofmechanical-to-electrical energy conversion such as electromagnetic,piezoelectric, or electrostatic do not allow for effective directcoupling to most of the high power environmental mechanical energysources. Bulky and expensive mechanical or hydraulic transducers arerequired to convert a broad range of aperiodic forces and displacementstypically encountered in nature into a form accessible for conversionusing these methods.

Recently, a new approach to energy harvesting has been proposed thatsubstantially alleviates the above-mentioned problems, the new approachbeing the use of a microfluidics-based energy harvester. In particular,a high power microfluidics-based energy harvester is disclosed in U.S.Pat. No. 7,898,096 entitled “Method and Apparatus for Energy HarvestingUsing Micro fluidics” issued to T. N. Krupenkin on Mar. 2, 2011 andherein incorporated by reference.

Krupenkin discloses an apparatus comprising a mechanical-to-electricalenergy converting device having a plurality of electrodes and a fluidicbody which comprises spatially separated conductive and dielectricliquid regions. The fluidic body is configured to reversibly move as awhole with respect to the plurality of electrodes under the influence ofa mechanical force. Each cycle of the reversible motion of said fluidicbody causes multiple alternations of the amount of electrical chargeaccumulated by the electrodes, whereby generating electrical currentflow between the electrodes.

The apparatus of Krupenkin comprises two substrates and disposedsubstantially co-planar and separated by spacers and. Spacers and aredisposed in such a way as to form a channel. A plurality of electrodesis disposed on substrate and a plurality of electrodes, is disposed onsubstrate. Substrates and spacers can be made of any solid dielectricmaterial such as glass, textolite, or a solid plastic, includingpolycarbonate, polypropylene, or polytetrafluoroethylene. The electrodescan be made of any solid conductive material, such as gold or tantalum,or indium tin oxide glass. In some preferred embodiments comprise atantalum film or a gold film.

A movable fluidic body is disposed in channel and configured to slidealong channel past electrodes. Fluidic body consists of two immiscibleliquids, one being a dielectric liquid and the other one being anelectrically conductive liquid. Examples of suitable electricallyconductive liquids include aqueous salt solutions and molten salts.Exemplary aqueous salt solutions include 0.01 molar solutions of saltssuch as CuSO₄, LiCl, KNO₃, or NaCl. Exemplary molten salts include1-ethyl-3-methylimidazolium tetrafluoroborate and1-ethyl-3-methylimidazolium trifluoromethanesulfonate, which are bothcommercially available. In other cases the conductive liquid cancomprise liquid metals such as, gallium, indium or mercury. Examples ofsuitable dielectric liquids include silicone oils and alkanes. Exemplarysilicone oils include polydimethylsiloxane and polydiphenylsiloxane, andexemplary alkanes include nonane and heaxadecane.

Conductive and dielectric liquids are spatially separated in a pluralityof distinct regions. Dielectric liquid regions and conductive liquidregions are arranged in a periodic alternating pattern, such thatconductive and dielectric regions regularly alternate. The boundariesbetween immiscible liquid regions are preserved by the surface tensionforces, giving fluidic body an ability to move as a whole, e.g. slidealong channel without disturbing the arrangement and volume of theabove-mentioned distinct liquid regions.

The needs remaining in the art are addressed by the present invention,which relates to the harvesting of electrical energy from mechanical,vibrational movement and, more particularly, to the utilization of aplurality of microfluidic elements to convert vibrational energy intouseful electrical energy.

In accordance with an exemplary embodiment of the present invention, anarray of conductive liquid droplets is disposed on a base substrate andseparated from a dielectric-covered electrode by an elastic spacer,forming a capacitive array structure. The elastic spacer is periodicallycompressed in response to external vibrations, which in turn causes thedroplets to be periodically squeezed between the electrode and basesubstrate. The droplet compression increases the contact area betweenthe droplets and the electrode, creating periodic changes in the amountof electrical charge accumulated between the electrodes, resulting inelectrical energy production in the form of a current flowing betweenthe electrodes.

In one case, a proof mass may be attached to the microfluidic energyharvester, where any vibrations impressed upon the proof mass will betranslated to the energy harvester and create periodic compression ofthe elastic spacer and compression of the plurality of conductivedroplets. Alternatively, a direct force (period in nature) may beapplied to the microfluidic energy harvester to generate electricalenergy from the periodic compression of the conductive droplets.

In an alternative embodiment, multiple arrays of elastic spacer andconductor, increasing the amount of energy that is produced for a givensurface area (i.e., “footprint”’).

In one instance, the present invention can be defined as an apparatusfor converting mechanical energy into electrical energy comprising aplurality of electrically conductive liquid droplets disposed in aplanar arrangement, a planar electrode disposed in a parallel,spaced-apart relationship with the plurality of electrically conductiveliquid droplets, a dielectric layer positioned between the plurality ofelectrically conductive liquid droplets and the planar electrode so asto form a capacitive structure therewith, an elastic spacer elementdisposed between the plurality of electrically conductive liquiddroplets and the planar electrode so as to surround the plurality ofelectrically conductive liquid droplets, such that the application ofmechanical energy to the apparatus compresses the elastic spacer elementand the plurality of electrically conductive liquid droplets, increasinga contact area between said plurality of electrically conductive liquiddroplets and the dielectric layer and also an overlap area with theplanar electrode, and an electrical circuit means, electrically coupledbetween the plurality of electrically conductive liquid droplets and theplanar electrode so as to apply a bias voltage therebetween and transferelectrical current generated in response to the change in capacitanceassociated with the change in overlap area to a power consuming element.

The present invention also describes a method of harvesting electricalenergy from vibrational motion by disposing a plurality of electricallyconductive liquid droplets on a substrate, covering the plurality ofelectrically conductive liquid droplets with a layer of dielectricmaterial, surrounding the combination of the electrically conductiveliquid droplets and layer of dielectric material with an elastic spacerelement, positioning a planar electrode over the dielectric material soas to form a capacitive structure with the dielectric material and theplurality of electrically conductive liquid droplets, applying apredetermined bias voltage between the planar electrode and theplurality of electrically conductive liquid droplets, and subjecting thearrangement to a periodic mechanical force so as to compress and thendecompress the elastic spacer and the plurality of electricallyconductive liquid droplets in a manner to periodically change thecapacitive value of the arrangement and create an electrical currentoutput therefrom.

WO 2008/109153 PCT/US2008/003064 entitled “Electrical Energy Generator”by Lemieux published Sep. 12, 2008 and herein incorporated by referencediscloses a device for harvesting mechanical energy from a moving massand converting the harvested mechanical energy into usable electricalenergy. The device permits the capture of mechanical energy imparted tothe device from movement, such as human gait activities, and theconversion of the captured mechanical energy into electrical energy. Thedevice may be used to provide power to a wide variety of electronicdevices.

Mechanical energy comprises a number of forms of energy including, butnot limited to kinetic energy. Mechanical energy is manifested in thebodies of humans and animals as a result of their physical processes.Such physical processes include voluntary body movements. Amongstvoluntary body movements are gait processes. Gait activities includestepping, walking, running, climbing, jumping, and similar activities.Other voluntary body movements include grasping, reaching, shaking,swinging, stretching, etc. All voluntary body movements are manifestedas motion of body members having mass so that all voluntary motoractivities develop kinetic energy. Further, voluntary motor activitiesmay impart kinetic energy to peripheral masses engaged with a movingbody.

It is often desirable to convert mechanical energy to electrical energy.An example is the conversion of kinetic energy into electrical energy asthe kinetic energy of a mass moves a magnetic field relative to aconductive coil thereby converting the kinetic energy of the mass toelectrical energy by action of electromagnetic induction.

Kinetic energy is manifested in the bodies of animals and humans, as aresult of different voluntary motor activities. Voluntary motoractivities include, for example, gait processes, leg movements, armmovements, head movements, torso movements, and the like. Kinetic energyis also manifested in the objects or masses that are moved by a human oranimal in the course of transporting them. Some voluntary motoractivities, such as human walking gait, are rhythmic activities whichhave a predictable frequency or periodicity. In the case of humanwalking gait, the predictable frequency is approximately 2 Hz.

An electrical energy generator for harvesting kinetic energy andconverting the harvested kinetic energy developed or imparted byvoluntary motor activities into electrical energy is provided. Theelectrical energy generator may generally comprise a housing, aninduction coil, an electromagnetically active mass movable in areciprocating manner relative to the housing, and at least one springengaging the electromagnetically active mass to the housing.

According to certain illustrative embodiments, the electrical energygenerator generally comprises a housing, an induction coil, anelectromagnetically active mass movable in a reciprocating mannerrelative to the housing, a first spring engaged with the mass and thehousing, and a second spring engaged with the mass and the housing.

According to further illustrative embodiments, the electrical energygenerator comprises a housing, an induction coil, an electromagneticallyactive mass movable in a reciprocating manner relative to the housing, afirst spring engaged with the mass and the housing, a second springengaged with the mass and the housing, wherein the electromagneticallyactive mass is constrained within the housing to minimize or otherwisesubstantially prevent non-reciprocating movement of the mass.

According to other illustrative embodiments, the electrical energygenerator comprises a housing, an induction coil, an electromagneticallyactive mass movable in a reciprocating manner relative to the housing, afirst spring engaged with the mass and the housing, and a second springengaged with the mass and the housing, and means of mitigating motionretardation of the electromagnetically active mass within the housing.

According to additional illustrative embodiments, the electrical energygenerator comprises a housing, an induction coil, an electromagneticallyactive mass movable in a reciprocating manner relative to the housing, afirst spring engaged with the mass and the housing, and a second springengaged with the mass and the housing, and at least one springdeflection adjustor.

It should be noted that the electrical energy generator may include acombination of two or more of means for constraining thenon-reciprocating movement of the electromagnetically active mass withinthe housing, means for mitigating motion retardation of theelectromagnetically active mass within the housing, and at least onespring deflection adjustor.

The device harvests mechanical energy and converts the harvestedmechanical energy into electrical energy. By harvesting mechanicalenergy from the reciprocating mass and converting it into electricalenergy, the device acts as a linear electrical generator. The generatedelectrical energy may be used to power a wide variety of electronicdevices including, without limitation, locators, signaling equipment,entertainment equipment, energy storage equipment, radio receivers,radio transmitters, wireless telephones, cameras, global positioningsystem (GPS) equipment, and like electronic devices.

It is readily appreciated that although examples of dosimetry processingdevices are disclosed herein, they may be implemented on any suitablecomputer system or computing device. It is to be understood that thedevices and systems of the examples described herein are for exemplarypurposes, as many variations of the specific hardware and software usedto implement the examples are possible, as will be appreciated by thoseskilled in the relevant art(s). Furthermore, the system of the examplesmay be conveniently implemented using one or more general purposecomputer systems, microprocessors, digital signal processors, andmicro-controllers, programmed according to the teachings of theexamples, as described and illustrated herein, and as will beappreciated by those ordinary skill in the art. The examples may also beembodied as a non-transitory computer readable medium havinginstructions stored thereon for one or more aspects of the presenttechnology as described and illustrated by way of the examples herein,as described herein, which when executed by a processor, cause theprocessor to carry out the steps necessary to implement the methods ofthe examples, as described and illustrated herein.

WO 2008/109153 PCT/US2008/003064 entitled “Event Dosimeter Device andMethods Thereof” by Borkholder et al. published Aug. 30, 2012 and hereinincorporated by reference discloses a power system that includes abattery coupled between a regulator and an energy harvester device,although other types of power systems with other types and numbers ofcomponents, such as one without an energy harvester and/or without aregulator could be used. In this example, the battery isnon-rechargeable and non-user replaceable so the dosimetry apparatus isdesigned to be disposable by way of example only, although other typesof batteries can be used, such as a user-replaceable and rechargeablebatteries. With this exemplary disposable design and the associatedlower cost, multiple dosimetry apparatuses may be utilized on eachperson to improve the quality of the collected data and the resultinginjury risk assessments. Additionally, with this disposable design forthis example of the dosimetry apparatus it is easier to incorporatedesign changes and update algorithms as the dosimetry apparatus isrolled out for product shipments. As a result, with this exemplarydesign the latest version always is being delivered out to customers inthe field, while traditional (non-disposable) systems would have tosomehow incorporate an upgrade. The regulator is coupled to regulatepower provided by the battery to the dosimetry processing device. Theenergy harvester device, such as solar or vibration energy device by wayof example only, can be used to supply power to the system and/orrecharge the battery, although other types and numbers of energyharvester devices could be used.

An optional wireless location determination system is coupled to thedosimetry processing device to provide location data for the dosimetryapparatus, which can be correlated with and stored with the obtainedsensor readings. Examples of location determination systems include aglobal position system (GPS) or positioning systems based upontriangulation of wireless signals from base stations or other wirelessbeacons; other types and numbers of location determination systems couldalso be used.

Thus, in one embodiment, the present invention employs an energyharvester that converts light energy into electrical energy suitable foruse in a wireless sensor.

In another embodiment, the present invention employs an energy harvesterthat converts mechanical vibrational energy into electrical energysuitable for use in a wireless sensor. The mechanical vibrational energymay be due to human motion, the motion of a human limb or other activityby a human. The mechanical vibrational energy may also be caused by thevibrations of a machine or infrastructure on which a wireless sensor ismounted.

In yet another embodiment, the present invention employs an energyharvester that converts light generated by any source such as the sun(solar energy), artificial lighting, a laser beam focused on the device,etc. into energy.

In yet another embodiment, the present invention employs an energyharvester that converts an radiofrequency radiation from RF-emittingsources into energy.

In yet another embodiment, the present invention employs an energyharvester that uses a thermocouple to convert heat from the human body,from a machine, from a combustive device or generated by human motioninto electrical energy suitable for use in a wireless sensor.

In still another embodiment, the present invention employs an energyharvester that converts radiofrequency energy into electrical energysuitable for use in a wireless sensor. In some embodiments, aradiofrequency receiver coil of the energy harvester may be adjusted tooptimize the harvesting of radiofrequency energy. Integration of thereceiver coils and sensors into piece of fabric, such as a piece ofclothing, may be done in order to maximize energy collection and sensingcapabilities. Furthermore, the radiofrequency receiver may be disclosed,for example, on a printed circuit board (PCB) such as in a holdersurrounding a prescribed electrical device such as a dosimeter. In adisclosed embodiment, the size and shape of the radiofrequency receivingantenna may be embedded in the holder and can be adjusted to optimizethe collection of RF energy.

In yet another embodiment, the present invention employs an energyharvester that has the ability to be adjusted to maximize the energycollected for a particular application. For example, a mechanical energyharvester using a magnet and coil, depending on the particularapplication, the size of the coil, the size and strength of the magnets,etc., may be adjusted.

Hardware components of the disclosed invention are further illustratedin FIG. 11 wherein modular sensors are integrated on a single chip orelectronic board 1102 (e.g., PCB) thus forming an integrated sensormodule 1100. Integrated sensor module 1100 collects radiation data andis configured to ultimately transmit the data to a remote location suchas a wireless base station or other wireless communications device. Theintegrated sensor module 1100 is designed to be an independent sensorsystem that can be incorporated into many different form factor devices.The small size and self-contained nature of the integrated sensor module1100 to be integrated into a wide range of devices such as a badge,nametag, key chain, bracelet, wrist watch, portable electronic device,MP3 Player, pager, cell phone, smartphone, laptop, tablet, glasses,article of clothing, wallet, purse or jewelry.

The primary sensor array 1120 can either be a single sensor, a lineararray of sensors, or a matrix of sensors to form the primary or modularsensor array 1104, for example employed from the sensor array 100 ofFIG. 1. Thus the modular sensor array 1104 may utilize only a firstsensor #1 (1112). Alternatively, modular sensor array 1104 may comprisen number of rows such as from first sensor #1 (1112) to sensor # n(1114). Alternatively and/or in addition, modular sensor array 1104 mayinclude m number of columns such as from first sensor #1 (1112) tosensor # m (1116). Thus, having n number of rows and m number ofcolumns, modular sensor array 1104 would extend from first sensor #1(1112) to sensor # m, n (1118).

While ionizing radiation sensors 102 encapsulated within “filtrationbubbles” 108 are shown for illustrative purposes, those skilled in theart will readily appreciate that the primary sensor array 1120 mayconsist of other suitable types of sensors (e.g., for non-ionizingradiation, hazardous chemicals, or other biochemical substances).Alternative embodiments of the disclosed invention may also includechemical or other sensors in addition and/or as an alternative toionizing radiation sensor 102. The present invention describes anintegrated sensor module 1100 that provides unique information about thelocation and the motion of the sensor when a measurement is obtained.The modular nature of the described platform and device enables the useof other individual sensors or as variable combination of sensors chosento meet the needs of potential end users. The modularity is achieved bydeveloping the measurement devices as interchangeable modules that canbe coupled to a central processing unit (CPU) that handles thecollection of time, motion, position and temperature and thecommunication.

The primary sensor array 1120 may be integrated with a global positionsensor package 1106. The global position sensor package 1106 comprises aglobal positioning system (GPS) radio that will determine its positionby either the on-board GPS radio and/or by a connected wireless-enabledmobile device (e.g., smartphone or tablet with GPS sensing capability,etc.) or by estimation through a mesh of networked devices. To minimizepower consumption of the primary power source the device willpreferentially determine location through GPS sensors with the lowestpower means available to it. First by the connected wireless-enabledmobile device with GPS capability, second by onboard GPS sensor andthird by estimation through a mesh of networked devices. Integratedsensor module 1100 includes one or more motion sensors in motion sensorpackage 1132. In one embodiment, motion sensor package 1132 includessingle 3-axis MEMS based accelerometer that will determine if a primarydata exposure occurs while the device is stationary or in motion asmeasured on a continual basis. A primary data exposure is a radiologicalevent recorded by the primary sensor array 1120. Integrated sensormodule 1100 includes a computer 1142 comprising a processor 1144 forprocessing data from the sensors from modular sensor array 1104, globalposition sensor package 1106 and motion sensor package 1132.

Computer 1142 may transfer this data wirelessly to second computer (notshown) or other electronic device (not shown) via wireless system on achip (SOC) module 1108. The second computer or other electronic devicemay process the data and/or display the data to a user either before orafter processing the data. For example, motion data from motion sensorpackage 1132 may be processed by computer 1142 and wirelessly sent to asecond computer or other electronic device. Alternatively, wireless SOCmodule 1108 may be used to transfer unprocessed data from modular sensorarray 1104, global position sensor package 1106 and motion sensorpackage 1132 to a second computer or other electronic device foradditional processing and/or displaying to a user. For example, motiondata from motion sensor package 1132 may be wirelessly sent to a secondcomputer or other electronic device, such as the mobile communicationdevice or the remote data server shown in FIG. 3 or the distributed dataserver shown in FIG. 8, for processing and/or displaying to a user. Inaddition to motion data, motion sensor package 1132 may also provide tocomputer 1142 or to the second computer identification data relating tothe individual wearing integrated sensor module 1100

A wireless system on a SOC module 1108 is configured to integratedsensor module 1100. The wireless SOC module 1108 is an integratedpackage consisting of a central processing unit and the wirelesstransceiver. Combining the wireless transceiver into the CPU chip in aSOC configuration allows a reduction in footprint and energyconsumption. The wireless system on a SOC module 1108 permits wirelesstransmission from integrated sensor module 1100, for example, to awireless receiver of another electronic device for electroniccommunication purpose(s). Such communications ability facilitatesefforts, for example, in determining whether integrated sensor module1100 is within range of the aforementioned electronic device as furtherdiscussed below.

The power harvester 1110 may include one or more energy harvestingdevices. A power harvester 1110 is incorporated into the integratedsensor module 1100 and connected to the battery. Power harvester 1110collects energy via motion and/or movement of the integrated sensormodule 1100 and the ambient light to recharge the battery that suppliespower to electronic board 1102. Thus, the present invention willactively consume power as it operates and actively communicates toexternal wireless enabled devices. Power harvester 1110 leveragesexisting work within the MEMS devices to convert periodic (resonant)vibrational mechanical motion into electrical energy to extend thebattery that powers the runtime of the radiation measurement sensorcapability of the integrated sensor module 1100.

U.S. Patent Application No. 2012/0271121 to Della Tone et al. entitled“INTEGRATED BIOMETRIC SENSING AND DISPLAY DEVICE” describes one type ofmotion sensor that may be used as a motion sensor in an integratedsensor module of the present invention and the entire contents anddisclosure of this application is incorporated herein by reference. Sucha motion sensor may detect motion by measuring one or more ofrectilinear and rotational acceleration, motion or position of theradiation sensor device. In other embodiments, the motion sensor mayalso measure a change in rectilinear and rotational speed or vector ofthe radiation sensor device. In one embodiment, the motion sensor maydetect motion along at least three degrees of freedom. In otherembodiments, the motion sensor may detect motions along six degrees offreedom, etc. The motion sensor may include a single, multiple orcombination axis accelerometer to measure the magnitude and direction ofacceleration of a motion.

The motion sensor may also include a multi-axis gyroscope that providesorientation information. The multi-axis gyroscope measures rotationalrate (d(angle)/dt, [deg/sec]), which may be used to determine if aportion of a body of the user is oriented in a particular directionand/or be used to supplement information from an accelerometer todetermine a type of motion performed by the user based on the rotationalmotion of a user. For example, a walking motion may cause a “pendulum”motion at a wrist of the user, whereas a running motion may cause acyclic motion at the user wrist along an axis lateral to a directiondetected by an accelerometer. Additionally, the motion sensor may useother technologies such as magnetic fields to capture orientation ormotion of a user along several degrees of freedom. In one embodiment,the motion sensor sends electrical signals to a processor providingdirection and motion data measured by the sensor.

Data about the motion of an individual wearing an integrated sensormodule including a motion sensor my processed using a computer orprocessor that is part of the integrated sensor module and/or by aseparate processor or computer that is in wired or wirelesscommunication with the integrated sensor module. The wired or wirelesscommunication may be in real-time. Motion data from the motion sensormay also be transferred from the integrated sensor module to a computerfor processing using a storage medium such as a flash memory card orflash memory stick.

In one embodiment, the present invention provides a method and acomputer configured to implement a method in which accelerometerdisplacement measurements (motion activity) is correlated with clockoutput (time) to determine the period during which an individual wasactive. This information can in turn be used to determine if aparticipant was wearing the dosimeter during their designated workperiod.

In one embodiment, the present invention provides a method and acomputer configured to implement a method in which accelerometerdisplacement measurements (motion activity) is correlated with clockoutput (time) and with measurements of the on-board sensors (exposure)to determine if the participant was wearing the dosimeter when it wasexposed.

In one embodiment, the present invention provides a method and acomputer configured to implement a method in which accelerometerdisplacement measurements (motion activity) are correlated with spatialposition (based on data from a GPS or based on data from a positionbeacon, such as a Bluetooth position beacon) and with exposure todetermine if the individual was in an occupationally-monitored worklocation when the dosimeter was exposed.

In one embodiment, the present invention provides a method and acomputer configured to implement a method in which motion activitymeasured by multiple motion sensors is analyzed to determine where onthe body of an individual the individual was wearing a dosimeter whenthe dosimeter was exposed to radiation.

In one embodiment, the present invention provides a method and acomputer configured to implement a method in which motion activitymeasured by multiple motion sensors to obtain a biometric signature foran individual is analyzed to determine: (1) if the individual wearingthe dosimeter was not the person to whom the dosimeter was assigned and(2) the probability that the individual wearing the dosimeter was theperson to whom the dosimeter was assigned.

In one embodiment of the invention, the motion data obtained from one ormore motion sensors of dosimeter, such an integrated sensor module, mayfunction as a type of biometric data used to identify an individual. Themotion sensors may include various types of motion sensors such anaccelerometer, a gyroscope, an energy harvest, etc. For example, theremay be an existing database containing motion data for the individualsto whom the integrated sensor modules have been assigned. This databasemay be generated based previous motion data from individuals wearingintegrated sensor modules or by using other devices with motion sensorsto generate this data for the individuals in the database. By comparingthe motion data obtained by the one or more motion sensors of theintegrated sensor module to the motion data in the in the database, thecomputer may: (1) determine the identity of the individual (if identitydata for the individual wearing the integrated sensor module is not sentalong with the motion data sent to the computer) or confirm the identityof the individual (if identity data for the individual wearing theintegrated sensor module is sent along with the motion data sent to thecomputer) and (2) determine if only a single individual has been wearingthe integrated sensor module. In the case of determining the identity ofthe individual, the motion data from multiple sensors, such as from theaccelerometer, from a gyroscope, or from an energy harvester, may becompared to motion data for a plurality of individuals in a database tofind a best match. In the case of confirming the identity of anindividual, the motion data has identity data for the individualassociated with the motion data and the motion data is compared againstexisting motion data for the individual in the data base.

In one embodiment of the present invention, motion data may be analyzedand used to estimate the probability that the dosimeter was worn by anindividual to whom it had been assigned (versus the probability that itwas worn by someone other than the participant to whom it had beenassigned). Supervised machine learning techniques may be used to train acomputer program to classify the data as indicating that a dosimeter hasor has not been worn by an individual. Unsupervised machine learningtechniques may be used to estimate the probabilities that an individualhas worn a dosimeter.

In one embodiment of the present invention, motion data may be generatedby motion sensors based upon an individual's motion-activity patternsthroughout the course of the work day, such as the individual's walkinggait, the individual's breathing pattern, and any characteristicmotion-related habits that the individual may have. Previous work hasdemonstrated the ability to distinguish motion activity for staticpostures such as standing, sitting, or lying-down, and dynamic posturessuch as walking, running, climbing stairs, bicycling, and driving in amotorized vehicle. In an example of the present invention, theindividual might usually be standing at work, or the individual mightstand at a particular time of the day and sit-down at another time ofthe day. Another example is that an individual might operate machinerythat has a characteristic pattern of vibration or motion that can beused to identify deviations from normal use of the dosimeter.

In one embodiment of the present invention a computer may be configuredto determine the period(s) of time that an individual has worn theintegrated sensor module based on the motion data obtained by the one ormore motion sensors of an integrated sensor module and time data from aclock that is on-board the dosimeter or part of a computer being used toanalyze the motion data from the motion sensors of the dosimeter.

In one embodiment of the present invention, machine learning algorithmsmay be used to extract information from the sensor data in order tocharacterize the motion-activity patterns of individual participants,and in order to correlate motion-activity with other exposure events.

The present invention will now be described by way of the followingnon-limiting examples.

EXAMPLES Example 1

U.S. Pat. No. 7,777,396 B2 entitled “IMPACT POWERED DEVICES” issued toRastegar et al. on Aug. 17, 2010 and herein incorporated by referencedescribes a sensor device includes an energy harvester for convertingmechanical vibrational energy into electrical energy suitable for use ina wireless sensor of the sensor device. Described embodiments include ahousing; a powered element disposed on or in the housing; and an impactpower producing element housed on or in the housing and operativelyconnected to the powered element, the impact power producing elementproducing power upon an impact of at least a portion of the housing withanother surface. The energy harvester uses magnet and coil.

Example 2

U.S. Pat. Application Pub. No. 2012/0319404 A1 entitled “BATTERYASSEMBLY WITH KINETIC ENERGY-BASED RECHARGING” by Joseph et al.published Dec. 20, 2012 and herein incorporated by reference disclosesanother sensor device includes an energy harvester for convertingmechanical vibrational energy into electrical energy suitable for use ina wireless sensor of the sensor device. Described embodiments include amobile electronic device configured to recharge when oscillated. Theelectronic device includes a housing with a battery compartment and abattery assembly positioned within the battery compartment. The batteryassembly includes a rechargeable storage battery connected to device'sbattery contacts. The battery assembly includes a charging assemblyconnected to the rechargeable storage battery, and the charging assemblyprovides a kinetic energy-based generator operating during theoscillating motion of the electronic device to output electrical currentto the rechargeable storage battery. The generator includes: (a) abarrel; (b) a permanent magnet positioned in an elongated chamber of thebarrel and sliding within the chamber during movement of the device; and(c) a coil of conductive wire wrapped around an outer surface of thebarrel. The chamber, generator magnet, and barrel outer surfacereceiving the coil all may be non-circular in cross sectional shape ornon-cylindrical to improve kinetic energy harvesting. The energyharvester uses magnet and coil design.

Example 3

An example of an alternative type of energy harvester that can beminiaturized and used to power sensors mounted in discrete locationsincluding, for example, on a vehicle or a cargo container includes U.S.Pat. Application Pub. No. 2009/0080138 A1 entitled “FLUIDICELECTROSTATIC ENERGY HARVESTER” by Lohndorf et al. published Mar. 26,2009 and herein incorporated by reference. A variable capacitor isdisclosed that operates without moving mechanical parts. In thiscapacitor electrically conductive electrodes are separated by anenclosed chamber filled with an electrically conductive material. Theelectrically conductive material can freely vary its position within thechamber. The capacitance of the device will vary as position of theconductive material changes due to external mechanical motion (ex:rotation vibration, etc.) of the device.

Example 4

An example of an energy harvester based upon high-output, organicfilm-based photovoltaic cells includes EP 2 378 581 B1 entitled“PHOTOVOLTAIC CELL” by Carroll published Jul. 31, 2013 and hereinincorporated by reference.

Example 5

A sensor device includes an energy harvester having a thermocouple forconverting heat from a human body into electrical energy suitable foruse in a wireless sensor of the sensor device. U.S. Pat. ApplicationPub. No. 2013/0312806 A1 entitled “THERMOELECTRIC APPARATUS ANDAPPLICATIONS THEREOF” by Carroll published Nov. 28, 2013 and hereinincorporated by reference discloses a thermoelectric apparatus andvarious applications of thermoelectric apparatus. The thermoelectricapparatus comprises at least one p-type layer coupled to at least onen-type layer to provide a pn junction, and an insulating layer at leastpartially disposed between the p-type layer and the n-type layer, thep-type layer comprising a plurality of carbon nanoparticles and then-type layer comprising a plurality of n-doped carbon nanoparticles.

Example 5

A sensor device includes an energy harvester for convertingradiofrequency energy into electrical energy suitable for use in awireless sensor of the sensor device. The energy harvester hasradiofrequency receiver coils that are integrated in the fabric of apiece of clothing in order to maximize energy collection and sensingcapabilities (See information provided athttp://www.wfu.edu/nanotech/News.html which is incorporated hereinincorporated by reference.

Example 6

A sensor device includes an energy harvester for converting lightgenerated by any source including sunlight (solar energy), artificiallighting or laser beam into electrical energy suitable for use in awireless sensor of the sensor device.

Example 7

Additional examples of mechanical energy harvesters include:

U.S. Pat. No. 8,704,387 B2 entitled “ELECTRICAL ENERGY GENERATOR” issuedto Lemieux on Apr. 22, 2014 and herein incorporated by referencedescribes an electrical energy generator comprising a housing having alongitudinal axis and opposite ends, an electromagnetically active masspositioned within the housing reciprocally movable along at least aportion of the longitudinal axis, an electrically conductive materialwithin the housing, a body engaged with the electromagnetically activemass, and at least one spring positioned between at least one of an endof the housing and an end of the body, or between an end of the body andthe electrically conductive material.

U.S. Pat. No. 8,674,526 B2 entitled “ELECTRICAL ENERGY GENERATOR” issuedto Lemieux on Mar. 18, 2014 and herein incorporated by referencedescribes an electrical energy generator including a housing, anelectromagnetically active mass positioned within the housing, anelectrically conductive material within the housing, a body positionedwithin the housing wherein the body and the electromagnetically activemass move relative to each other, and at least one spring for impartingrestorative forces to the electromagnetically active mass and the body.

Thus, disclosed embodiments relate generally to a power source forsensors. More specifically, the invention relates to an energy harvesterthat converts mechanical vibration, light, heat (e.g., heat from a body,a combustion device, or other heat-generating thermocouples),radiofrequency, or other forms of energy into electrical energy suitablefor use in small, wireless autonomous devices, for example, portablesensors, wearable electronics, motion sensors, wireless sensor networks,sensor-enabled fabrics and other wearable, portable or mobile products.

Example 8

An example of using accelerometer sensor data to obtain information thatcan be used to characterize the activity of individuals based uponcharacteristic motion patterns (activity recognition) is described inRavi N, Dandekar N, Mysore P, Littman M L, “Activity Recognition fromAccelerometer Data,” American Association for Artificial Intelligence,2005 (hereinafter “Ravi et al.” FIG. 3 of Ravi et al. shows a graph ofaccelerometer data classified by activity).

Example 9

An example of using multiple sensors, including accelerometer, audiomicrophone, and video camera to obtain different types of informationthat can be used to characterize the activity of individuals isdescribed in Casale P, Pujol O, Radeva P, “Human Activity Recognitionfrom Accelerometer Data Using a Wearable Device,” LNCS, 6669, 289-296,2011 (hereinafter “Casale et al.”) Casale, et al, incorporate amicrophone and video camera (with audio and video post-processing) tohelp characterize motion activities.

Example 10

An example of using accelerometer sensor data to obtain biometricinformation that can be used to identify individuals based uponcharacteristic walking patterns (biometric gait) is described in GafurovD, Helkala K, Sondrol T, “Biometric Gait Authentication UsingAccelerometer Sensor,” Journal of Computers, 1(7):51-59, 2006(hereinafter “Gafurov et al.”). Gafurov et al. demonstrates the abilityto distinguish between different individuals by performing a histogramsimilarity metric and a cycle length metric to accelerometerdisplacement data acquired from a three-axis accelerometer positioned onthe participant's leg.

Example 11

Mannini A, Sabatini A M, “Machine Learning Methods for Classifying HumanPhysical Activity from On-body Accelerometers,” Sensors, 10:154-1175,2010 provides a review of the machine-learning methods that have beendeveloped to classify human motion activity, please see the followingreference:

Example 12

An example of using accelerometer sensor data to obtain motioninformation that can be used to identify the mode of transportation bywhich an individual is moving is described in Bedogni L, Di Felice M,Bononi L, “By Train or By Car? Detecting the User's Motion Type throughSmartphone Sensors Data,” IEEE, 2012 (hereinafter “Bedogni et al.”)Bedogni et al. demonstrates the ability to use the accelerometer data ina smartphone to determine if the individual was walking, driving in acar, or riding in a train. This approach could be used to characterizethe motion of other types of motorized vehicles. In one embodiment, thepresent invention may be used to monitor non-living entities such astransport vehicles and cargo containers to identify and prevent thepotentially illegal transportation or storage of hazardous substances.

Example 13

FIG. 12 shows an exemplary graph of accelerometer displacement in thex-axis of direction, the y-axis of direction and the z-axis of directionvs. time of an accelerometer that is one of the motion sensors of adosimeter. When a person is not active or the dosimeter is not worn bythe individual, there is no or minimal displacement in the x-axis ofdirection, the y-axis of direction and the z-axis of direction as shownin the period of time labeled “No Activity”. During the time periodlabeled “Activity Level 1” there are frequent changes in the directionof motion of the accelerometer along x-axis of direction, less frequentchanges in direction of motion along the z-axis of direction andvirtually no change in motion along the z-axis of direction. In the timeperiod labeled “Activity Level 2” there are moderate amounts of changesin the direction of motion along the x-axis of direction, the y-axis ofdirection and the z-axis of direction.

Example 14

FIGS. 13, 14 and 15 shows exemplary graphs of accelerometer displacement(acceleration) in the x-axis of direction, the y-axis of direction andthe z-axis of direction vs. time of an accelerometer that is one of themotion sensors of a dosimeter. FIG. 13 shows the displacement of theaccelerometer when an individual wearing a dosimeter is sitting withminimal or no motion. In FIG. 13 there is no or minimal displacement inthe x-axis of direction, the y-axis of direction and the z-axis ofdirection. FIG. 14 shows the displacement of the accelerometer when anindividual wearing a dosimeter is walking. In FIG. 14, small amounts ofmotion occur along all three axes of direction as shown by the frequentsmall amplitude changes in displacement. FIG. 15 shows the displacementof the accelerometer when an individual wearing a dosimeter standswithout moving followed by the individual moving the individual's armsand then followed by the individual standing again. During the period ofthe individual moving the individual's arms, indicated by dashed oval1512 in FIG. 15, significant amounts of motion occur along all threeaxes of direction as shown by the frequent small amplitude changes indisplacement.

The devices and subsystems of the disclosed exemplary embodiments canstore information relating to various processes described herein. Thisinformation can be stored in one or more memories, such as a hard disk,optical disk, magneto-optical disk, RAM, and the like, of the devicesand subsystems of the disclosed exemplary embodiments. One or moredatabases of the devices and subsystems of the disclosed exemplaryembodiments can store the information used to implement the exemplaryembodiments of the present invention. The databases can be organizedusing data structures (e.g., records, tables, arrays, fields, graphs,trees, lists, and the like) included in one or more memories or storagedevices listed herein. The processes described with respect to thedisclosed exemplary embodiments can include appropriate data structuresfor storing data collected and/or generated by the processes of thedevices and subsystems of the disclosed exemplary embodiments in one ormore databases thereof.

All or a portion of the devices and subsystems of the disclosedexemplary embodiments can be conveniently implemented using one or moregeneral purpose computer systems, microprocessors, digital signalprocessors, micro-controllers, and the like, programmed according to theteachings of the exemplary embodiments of the present invention, as willbe appreciated by those skilled in the computer and software arts.Appropriate software can be readily prepared by programmers of ordinaryskill based on the teachings of the exemplary embodiments, as will beappreciated by those skilled in the software art. In addition, thedevices and subsystems of the disclosed exemplary embodiments can beimplemented by the preparation of application-specific integratedcircuits or by interconnecting an appropriate network of conventionalcomponent circuits, as will be appreciated by those skilled in theelectrical art(s). Thus, the exemplary embodiments are not limited toany specific combination of hardware circuitry and/or software.

Stored on any one or on a combination of computer readable media, theexemplary embodiments of the present invention can include software forcontrolling the devices and subsystems of the disclosed exemplaryembodiments, for driving the devices and subsystems of the disclosedexemplary embodiments, for enabling the devices and subsystems of thedisclosed exemplary embodiments to interact with a human user, and thelike. Such software can include, but is not limited to, device drivers,firmware, operating systems, development tools, applications software,and the like. Such computer readable media further can include thecomputer program product of an embodiment of the present invention forperforming all or a portion (if processing is distributed) of theprocessing performed in implementing the disclosed exemplaryembodiments. Computer code devices of the exemplary embodiments of thepresent invention can include any suitable interpretable or executablecode mechanism, including but not limited to scripts, interpretableprograms, dynamic link libraries (DLLs), Java classes and applets,complete executable programs, Common Object Request Broker Architecture(CORBA) objects, and the like. Moreover, parts of the processing of theexemplary embodiments of the present invention can be distributed forbetter performance, reliability, cost, and the like.

As stated above, the devices and subsystems of the disclosed exemplaryembodiments can include computer readable medium or memories for holdinginstructions programmed according to the teachings of the presentinvention and for holding data structures, tables, records, and/or otherdata described herein. Computer readable medium can include any suitablemedium that participates in providing instructions to a processor forexecution. Such a medium can take many forms, including but not limitedto, non-volatile media, volatile media, transmission media, and thelike. Non-volatile media can include, for example, optical or magneticdisks, magneto-optical disks, and the like. Volatile media can includedynamic memories, and the like. Transmission media can include coaxialcables, copper wire, fiber optics, and the like. Transmission media alsocan take the form of acoustic, optical, electromagnetic waves, and thelike, such as those generated during radio frequency (RF)communications, infrared (IR) data communications, and the like. Commonforms of computer-readable media can include, for example, a floppydisk, a flexible disk, hard disk, magnetic tape, any other suitablemagnetic medium, a CD-ROM, CDRW, DVD, any other suitable optical medium,punch cards, paper tape, optical mark sheets, any other suitablephysical medium with patterns of holes or other optically recognizableindicia, a RAM, a PROM, an EPROM, a FLASH-EPROM, any other suitablememory chip or cartridge, a carrier wave, or any other suitable mediumfrom which a computer can read.

While the present invention has been disclosed with references tocertain embodiments, numerous modifications, alterations, and changes tothe described embodiments are possible without departing from the spiritand scope of the present invention, as defined in the appended claims.Accordingly, it is intended that the present invention not be limited tothe described embodiments, but that it has the full scope defined by thelanguage of the following claims, and equivalents thereof.

REFERENCES

-   1. S. R. Anton, H. A. Sodano, A review of power harvesting using    piezo-electric materials (2003-2006), Smart Mater. and Struct.    16 (3) (2007) R1-R21. doi: 10.1088/0964-1726/16/3/R01.-   2. S. P. Beeby, M. J. Tudor, N. M. White, Energy harvesting    vibration sources for microsystems applications, Meas. Sci. and    Tech. 17 (12) (2006) R175-R195. doi:10.1088/0957-0233/17/12/R01.-   3. P. Mitcheson, E. Yeatman, G. Rao, A. Holmes, T. Green, Energy    Harvesting From Human and Machine Motion for Wireless Electronic    Devices, Proceedings of the IEEE 96 (9) (2008) 1457-4486.    doi:10.1109/JPROC.2008.927494.-   4. S. Roundy, P. K. Wright, A piezoelectric vibration based    generator for wireless electronics, Smart Mater. and Struct.    13 (5) (2004) 1131-1142.-   5. A. Erturk, D. J. Inman, An experimentally validated bimorph    cantilever model for piezoelectric energy harvesting from base    excitations, Smart Materials and Structures 18 (2) (2009) 025009.-   6. D. F. Berdy, P. Srisungsitthisunti, B. Jung, X. Xu, J. F.    Rhoads, D. Peroulis, Low-frequency meandering piezoelectric    vibration energy harvester, IEEE transactions on ultrasonics,    ferroelectrics, and frequency control 59 (5) (2012) 846-58.    doi:10.1109/TUFFC.2012.2269.-   7. C. Williams, R. Yates, Analysis of a micro-electric generator for    microsystems, Proceedings of the International Solid-State Sensors    and Actuators Conference—TRANSDUCERS '95 44 (0) (1995) 369-372.    doi:10.1109/SENSOR.1995.717207.-   8. S. P. Beeby, R. N. Torah, M. J. Tudor, P. Glynne-Jones, T.    O'Donnell, C. R. Saha, S. Roy, A micro-electromagnetic generator for    vibration energy harvesting, J. Micromech. Microeng. 17 (7) (2007)    1257-1265.-   9. S. Roundy, P. Wright, J. Rabaey, A study of low level vibrations    as a power source for wireless sensor nodes, Computer Communications    26 (2003) 1131-1144.-   10. S. Meninger, J. Mur-Miranda, R. Amirtharajah, A.    Chandrakasan, J. Lang, Vibration-to-electric energy conversion, IEEE    Transactions on Very Large Scale Integration (VLSI) Systems    9 (1) (2001) 64-76.-   11. L. Wang, F. G. Yuan, Vibration energy harvesting by    magnetostrictive material, Smart Materials and Structures    17 (4) (2008) 045009.-   12. E. K. Reilly, L. M. Miller, R. Fain, P. K. Wright, A study of    ambient vibrations for piezoelectric energy conversion, in: Proc.    PowerMEMS, Washington D.C., 2009, pp. 312-315.-   13. S. Lam Po Tang, Recent developments in flexible wearable    electronics for monitoring applications, Transactions of the    institute of Measurement and Control 29 (3-4) (2007) 283-300.    doi:10.1177/0142331207070389.-   14. B. Lo, S. Thiemjarus, R. King, G. Yang, Body sensor network: a    wireless sensor platform for pervasive healthcare monitoring,    Conference on Pervasive Computing Technologies for Healthcare (2005)    77-80.-   15. K. Sun, G. Q. Liu, X. Y. Xu, Nonlinear Resonant Generator for    Harvesting Energy from Human Wrist Vertical Shaking, Applied    Mechanics and Materials 128-129 (2011) 923-927.    doi:10.4028/www.scientific.net/AMM.128-129.923.-   16. C. Saha, T. ODonnell, N. Wang, P. McCloskey, Electromagnetic    generator for harvesting energy from human motion, Sensors and    Actuators A: Physical 147 (1) (2008) 248-253,    doi:10.1016/j.sna.2008.03.008.-   17. P. Constantinou, P. H. Mellor, P. D. Wilcox, A Magnetically    Sprung Generator for Energy Harvesting Applications, IEEE/ASME    Transactions on Mechatronics 17 (3) (2012) 415-424.    doi:10.1109/TMECH.2012.2188834.-   18. X, Yang, B. Zhang, J. Li, Y. Wang, Model and Experimental    Research on an Electromagnetic Vibration-Powered Generator With    Annular Permanent Magnet Spring, IEEE Transactions on Applied    Superconductivity 22 (3) (2012) 5201504-5201504.    doi:10.1109/TASC.2011.2179401.-   19. A. R. M. Foisal, B.-C. Lee, G.-S. Chung, Fabrication and    performance optimization of an AA size electromagnetic energy    harvester using magnetic spring, 2011 IEEE SENSORS    Proceedings (2011) 1125-1128doi:10.1109/ICSENS.2011.6126947.-   20. P. Constantinou, P. Mellor, P. Wilcox, A Model of a Magnetically    Sprung Vibration Generator for Power Harvesting Applications, in:    2007 IEEE international Electric Machines & Drives Conference, IEEE,    2007, pp. 725-730. doi:10.1109/IEMDC.2007.382757.-   21. E. Dallago, M. Marchesi, G. Ventchi, Analytical Model of a    Vibrating Electromagnetic Harvester Considering Nonlinear Effects,    IEEE Transactions on Power Electronics 25 (8) (2010) 1989-1997.    doi:10.1109/TPEL.2010.2044893.-   22. B. Mann, N. Sims, Energy harvesting from the nonlinear    oscillations of magnetic levitation, Journal of Sound and Vibration    319 (1-2) (2009) 515-530. doi:101016/j.jsv.2008.06.011.-   23. A. R. M. Foisal, C. Hong, G.-S. Chung, Multi-frequency    electromagnetic energy harvester using a magnetic spring cantilever,    Sensors and Actuators A: Physical 182 (2012) 106-113.    doi:10.1016/j.sna.2012.05.009.-   24. G. P. Beyer, G. G. Mann, J. A. Pursley, E. T. Espenhahn, C.    Fraisse, D. J. Godfrey, M. Oldham, T. B. Carrea, N. Bolick,    and C. W. Scarantino, “An implantable MOSFET dosimeter for the    measurement of radiation dose in tissue during cancer therapy,” IEEE    Sensors Journal, vol. 8, 2008.

All publications, patent applications, patents, and other referencesmentioned in the specification are indicative of the level of thoseskilled in the art to which the presently disclosed subject matterpertains. All publications, patent applications, patents, and otherreferences are herein incorporated by reference to the same extent as ifeach individual publication, patent application, patent, and otherreference was specifically and individually indicated to be incorporatedby reference. It will be understood that, although a number of patentapplications, patents, and other references are referred to herein, suchreference does not constitute an admission that any of these documentsforms part of the common general knowledge in the art.

1-10. (canceled)
 11. A method comprising the following steps: (a)determining whether an individual was wearing a dosimeter during amonitored period based upon motion and time data obtained from thedosimeter, and (b) determining whether an individual was wearing thedosimeter when the dosimeter was exposed to one or more radiationsources based upon measured radiation dosage data for the dosimeter,motion data for the dosimeter, time data associated with the radiationdosage data, and time data associated with the motion data, (c)reporting whether the dosimeter was worn during a monitored period viadisplay on a visual display device and/or via saving whether theindividual was wearing a dosimeter when the dosimeter was exposed to oneor more radiation sources to a storage medium, and (d) reporting whetherthe individual was wearing a dosimeter when the dosimeter was exposed toone or more radiation sources via display on a visual display deviceand/or via saving whether the individual was wearing a dosimeter whenthe dosimeter was exposed to one or more radiation doses to a storagemedium.
 12. The method of claim 11, wherein the dosimeter comprises oneor more motion sensors for generating the motion data.
 13. The method ofclaim 12, wherein the one or more motion sensors comprise anaccelerometer and a gyroscope.
 14. The method of claim 11, wherein thedosimeter comprises a device for generating a location beacon andwherein the location data is based on data from the location beacon. 15.The method of claim 12, wherein the one or more motion sensors comprisean accelerometer.
 16. The method of claim 12, wherein the one or moremotion sensors comprise a a gyroscope.
 17. The method of claim 12,wherein the one or more motion sensors comprise an energy harvester. 18.A method comprising the following steps: (a) determining a dosimeter wasin a location when the dosimeter was exposed to one or more radiationdoses based on radiation dosage data for the dosimeter, motion data forthe dosimeter, time data associated with the radiation dosage data, timedata associated with the motion data, and location data and locationdata for the dosimeter, and (b) reporting whether the dosimeter was inthe location when the dosimeter was exposed to one or more radiationdoses via display on a visual display device and/or via saving whetherthe dosimeter was in the location when the dosimeter was exposed to oneor more radiation doses to a storage medium.
 19. The method of claim 18,wherein the dosimeter comprises one or more motion sensors forgenerating the motion data.
 20. The method of claim 19, wherein the oneor more motion sensors comprise an accelerometer and a gyroscope. 21.The method of claim 18, wherein the dosimeter comprises a device forgenerating a location beacon and wherein the location data is based ondata from the location beacon.
 22. The method of claim 19, wherein theone or more motion sensors comprise an accelerometer.
 23. The method ofclaim 19, wherein the one or more motion sensors comprise a gyroscope.24. The method of claim 19, wherein the one or more motion sensorscomprise an energy harvester.